ZeroToMastery - Complete A.I. Machine Learning and Data Science Zero to Mastery (4.2025)
File List
- 9. Scikit-learn Creating Machine Learning Models/17. NEW Choosing The Right Model For Your Data.mp4 164.6 MB
- 9. Scikit-learn Creating Machine Learning Models/40. NEW Evaluating A Model With Cross Validation and Scoring Parameter.mp4 142.2 MB
- 5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 140.0 MB
- 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 136.4 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Feature Engineering.mp4 122.5 MB
- 9. Scikit-learn Creating Machine Learning Models/43. Tuning Hyperparameters.mp4 121.7 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Turning Data Into Numbers.mp4 119.7 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictions.mp4 117.2 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/32. Training Your Deep Neural Network.mp4 115.3 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/21. Feature Importance.mp4 115.3 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Preproccessing Our Data.mp4 114.4 MB
- 16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.mp4 114.0 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/10. Finding Patterns 3.mp4 105.5 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/37. Visualizing And Evaluate Model Predictions 2.mp4 100.4 MB
- 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 100.3 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21. Turning Data Into Batches 2.mp4 99.0 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/40. Training Model On Full Dataset.mp4 98.5 MB
- 9. Scikit-learn Creating Machine Learning Models/50. Putting It All Together.mp4 96.9 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/35. Transform Predictions To Text.mp4 94.5 MB
- 9. Scikit-learn Creating Machine Learning Models/16. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 92.8 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/41. Making Predictions On Test Images.mp4 92.1 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data.mp4 91.6 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/22. Visualizing Our Data.mp4 91.4 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/22. Finding The Most Important Features.mp4 90.9 MB
- 5. Data Science Environment Setup/5. Mac Environment Setup.mp4 90.1 MB
- 9. Scikit-learn Creating Machine Learning Models/41. NEW Evaluating A Model With Scikit-learn Functions.mp4 90.0 MB
- 8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 86.4 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/39. Saving And Loading A Trained Model.mp4 86.0 MB
- 9. Scikit-learn Creating Machine Learning Models/45. Tuning Hyperparameters 3.mp4 85.3 MB
- 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4 85.3 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/42. Submitting Model to Kaggle.mp4 83.5 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 2.mp4 83.4 MB
- 9. Scikit-learn Creating Machine Learning Models/51. Putting It All Together 2.mp4 82.0 MB
- 9. Scikit-learn Creating Machine Learning Models/18. NEW Choosing The Right Model For Your Data 2 (Regression).mp4 80.8 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/15. Preparing The Images.mp4 80.2 MB
- 9. Scikit-learn Creating Machine Learning Models/34. NEW Evaluating A Classification Model 5 (Confusion Matrix).mp4 80.0 MB
- 5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 79.8 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25. Building A Deep Learning Model.mp4 79.0 MB
- 9. Scikit-learn Creating Machine Learning Models/21. Choosing The Right Model For Your Data 3 (Classification).mp4 78.3 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/9. Importing TensorFlow 2.mp4 78.1 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Numerical Values.mp4 77.9 MB
- 9. Scikit-learn Creating Machine Learning Models/44. Tuning Hyperparameters 2.mp4 76.8 MB
- 9. Scikit-learn Creating Machine Learning Models/36. NEW Evaluating A Regression Model 1 (R2 Score).mp4 75.7 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/16. Turning Data Labels Into Numbers.mp4 75.7 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14. Loading Our Data Labels.mp4 75.5 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/23. Reviewing The Project.mp4 74.6 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/15. Custom Evaluation Function.mp4 74.6 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/26. Building A Deep Learning Model 2.mp4 72.7 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.mp4 72.1 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/43. Making Predictions On Our Images.mp4 71.1 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27. Building A Deep Learning Model 3.mp4 70.9 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters.mp4 70.7 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/36. Visualizing Model Predictions.mp4 70.7 MB
- 9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Pandas.mp4 70.5 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/19. Preprocess Images 2.mp4 69.9 MB
- 8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 69.8 MB
- 8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 69.2 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 2.mp4 68.7 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/14. TuningImproving Our Model.mp4 68.3 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/13. Optional Reloading Colab Notebook.mp4 67.6 MB
- 9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Classification Model 6 (Classification Report).mp4 67.0 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Reducing Data.mp4 66.7 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.mp4 65.7 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18. Preprocess Images.mp4 65.6 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/38. Visualizing And Evaluate Model Predictions 3.mp4 65.4 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/12. Choosing The Right Models.mp4 64.9 MB
- 5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 2.mp4 64.3 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4. Setting Up Google Colab.mp4 63.5 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Project Environment Setup.mp4 63.2 MB
- 6. Pandas Data Analysis/10. Selecting and Viewing Data with Pandas Part 2.mp4 62.8 MB
- 9. Scikit-learn Creating Machine Learning Models/42. Improving A Machine Learning Model.mp4 62.4 MB
- 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 62.3 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. RandomizedSearchCV.mp4 62.3 MB
- 9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 62.2 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Splitting Data.mp4 62.1 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28. Building A Deep Learning Model 4.mp4 60.8 MB
- 7. NumPy/14. Exercise Nut Butter Store Sales.mp4 60.6 MB
- 6. Pandas Data Analysis/13. Manipulating Data 3.mp4 59.8 MB
- 7. NumPy/17. Turn Images Into NumPy Arrays.mp4 59.4 MB
- 9. Scikit-learn Creating Machine Learning Models/26. NEW Evaluating A Machine Learning Model (Score) Part 1.mp4 59.2 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Step 1~4 Framework Setup.mp4 58.6 MB
- 6. Pandas Data Analysis/4. Series, Data Frames and CSVs.mp4 58.0 MB
- 6. Pandas Data Analysis/11. Manipulating Data.mp4 57.5 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/20. Turning Data Into Batches.mp4 57.3 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Improving Hyperparameters.mp4 56.9 MB
- 8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.mp4 55.6 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/2. Deep Learning and Unstructured Data.mp4 55.4 MB
- 6. Pandas Data Analysis/12. Manipulating Data 2.mp4 54.7 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/20. Making Predictions.mp4 54.3 MB
- 7. NumPy/13. Dot Product vs Element Wise.mp4 53.9 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/33. Evaluating Performance With TensorBoard.mp4 53.8 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/6. Getting Our Tools Ready.mp4 53.8 MB
- 7. NumPy/9. Manipulating Arrays.mp4 53.6 MB
- 1. Introduction/1. Complete A.I. Machine Learning and Data Science Zero to Mastery.mp4 53.4 MB
- 8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 52.3 MB
- 13. Data Engineering/9. Optional OLTP Databases.mp4 52.1 MB
- 8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 51.9 MB
- 9. Scikit-learn Creating Machine Learning Models/25. NEW Making Predictions With Our Model (Regression).mp4 51.7 MB
- 9. Scikit-learn Creating Machine Learning Models/38. NEW Evaluating A Regression Model 3 (MSE).mp4 51.0 MB
- 9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 51.0 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Filling Missing Categorical Values.mp4 49.8 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/30. Evaluating Our Model.mp4 49.7 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/11. Using A GPU.mp4 48.8 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/17. Tuning Hyperparameters 3.mp4 48.1 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/7. Exploring Our Data.mp4 47.9 MB
- 1. Introduction/2. Course Outline.mp4 47.5 MB
- 9. Scikit-learn Creating Machine Learning Models/23. Making Predictions With Our Model.mp4 47.5 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/11. Preparing Our Data For Machine Learning.mp4 46.6 MB
- 6. Pandas Data Analysis/7. Describing Data with Pandas.mp4 46.3 MB
- 8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 45.9 MB
- 8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 45.9 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/21. Evaluating Our Model 3.mp4 43.9 MB
- 9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Classification Model 4 (Confusion Matrix).mp4 43.6 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model.mp4 43.3 MB
- 9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 2 (ROC Curve).mp4 41.3 MB
- 7. NumPy/8. Viewing Arrays and Matrices.mp4 41.2 MB
- 8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.mp4 41.2 MB
- 9. Scikit-learn Creating Machine Learning Models/27. NEW Evaluating A Machine Learning Model (Score) Part 2.mp4 40.7 MB
- 8. Matplotlib Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 40.7 MB
- 7. NumPy/5. Creating NumPy Arrays.mp4 40.5 MB
- 8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 40.3 MB
- 5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.mp4 40.2 MB
- 7. NumPy/4. NumPy DataTypes and Attributes.mp4 39.3 MB
- 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.mp4 39.2 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns.mp4 38.7 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17. Creating Our Own Validation Set.mp4 38.3 MB
- 9. Scikit-learn Creating Machine Learning Models/37. NEW Evaluating A Regression Model 2 (MAE).mp4 38.3 MB
- 7. NumPy/10. Manipulating Arrays 2.mp4 37.9 MB
- 9. Scikit-learn Creating Machine Learning Models/49. Saving And Loading A Model 2.mp4 37.7 MB
- 6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas.mp4 37.6 MB
- 9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 36.5 MB
- 9. Scikit-learn Creating Machine Learning Models/48. Saving And Loading A Model.mp4 36.3 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/13. Experimenting With Machine Learning Models.mp4 36.0 MB
- 9. Scikit-learn Creating Machine Learning Models/22. Fitting A Model To The Data.mp4 35.6 MB
- 3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp4 35.1 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Exploring Our Data 2.mp4 35.0 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6. Uploading Project Data.mp4 34.6 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/7. Setting Up Our Data.mp4 34.6 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Fitting A Machine Learning Model.mp4 34.5 MB
- 6. Pandas Data Analysis/15. How To Download The Course Assignments.mp4 34.1 MB
- 8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 33.9 MB
- 9. Scikit-learn Creating Machine Learning Models/24. predict() vs predict_proba().mp4 33.9 MB
- 7. NumPy/12. Reshape and Transpose.mp4 33.7 MB
- 8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 32.7 MB
- 7. NumPy/11. Standard Deviation and Variance.mp4 31.5 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/12. Optional GPU and Google Colab.mp4 31.3 MB
- 9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 3 (ROC Curve).mp4 30.0 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23. Preparing Our Inputs and Outputs.mp4 29.9 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/29. Summarizing Our Model.mp4 29.4 MB
- 7. NumPy/6. NumPy Random Seed.mp4 27.4 MB
- 5. Data Science Environment Setup/7. Windows Environment Setup.mp4 26.9 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5. Google Colab Workspace.mp4 26.4 MB
- 8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 24.4 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/20. Evaluating Our Model 2.mp4 24.1 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31. Preventing Overfitting.mp4 23.6 MB
- 2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 23.5 MB
- 2. Machine Learning 101/4. How Did We Get Here.mp4 23.0 MB
- 9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 22.9 MB
- 8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.mp4 22.0 MB
- 9. Scikit-learn Creating Machine Learning Models/47. Quick Tip Correlation Analysis.mp4 20.6 MB
- 13. Data Engineering/2. What Is Data.mp4 20.5 MB
- 3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 20.1 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/24. Exercise Imposter Syndrome.mp4 19.9 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.mp4 19.7 MB
- 7. NumPy/16. Sorting Arrays.mp4 19.6 MB
- 2. Machine Learning 101/1. What Is Machine Learning.mp4 19.2 MB
- 1. Introduction/5. Your First Day.mp4 18.8 MB
- 13. Data Engineering/7. Types of Databases.mp4 17.9 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/8. Setting Up Our Data 2.mp4 17.8 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 17.6 MB
- 9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 1 (Accuracy).mp4 17.4 MB
- 7. NumPy/15. Comparison Operators.mp4 17.3 MB
- 8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.mp4 17.2 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10. Optional TensorFlow 2.0 Default Issue.mp4 16.5 MB
- 3. Machine Learning and Data Science Framework/5. Types of Data.mp4 16.2 MB
- 3. Machine Learning and Data Science Framework/7. Features In Data.mp4 15.9 MB
- 2. Machine Learning 101/2. AIMachine LearningData Science.mp4 15.3 MB
- 7. NumPy/2. NumPy Introduction.mp4 15.3 MB
- 3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 15.2 MB
- 6. Pandas Data Analysis/3. Pandas Introduction.mp4 14.7 MB
- 3. Machine Learning and Data Science Framework/14. Tools We Will Use.mp4 14.6 MB
- 2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 14.6 MB
- 15. Storytelling + Communication How To Present Your Projects/5. Weekend Project Principle.mp4 14.0 MB
- 13. Data Engineering/5. What is a Data Engineer 3.mp4 13.6 MB
- 3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp4 12.7 MB
- 2. Machine Learning 101/6. Types of Machine Learning.mp4 12.7 MB
- 3. Machine Learning and Data Science Framework/13. Experimentation.mp4 12.0 MB
- 13. Data Engineering/4. What is A Data Engineer 2.mp4 11.4 MB
- 15. Storytelling + Communication How To Present Your Projects/2. Communicating Your Work.mp4 11.1 MB
- 2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 11.1 MB
- 15. Storytelling + Communication How To Present Your Projects/3. Communicating With Managers.mp4 10.9 MB
- 5. Data Science Environment Setup/2. Introducing Our Tools.mp4 10.8 MB
- 15. Storytelling + Communication How To Present Your Projects/4. Communicating With Co-Workers.mp4 10.6 MB
- 5. Data Science Environment Setup/4. Conda Environments.mp4 10.5 MB
- 3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp4 10.4 MB
- 9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4 10.1 MB
- 7. NumPy/1. Section Overview.mp4 9.8 MB
- 3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 9.8 MB
- 13. Data Engineering/3. What is a Data Engineer.mp4 9.4 MB
- 13. Data Engineering/13. Kafka and Stream Processing.mp4 9.3 MB
- 13. Data Engineering/6. What is a Data Engineer 4.mp4 8.8 MB
- 16. Career Advice + Extra Bits/7. JTS Start With Why.mp4 8.3 MB
- 15. Storytelling + Communication How To Present Your Projects/6. Communicating With Outside World.mp4 8.0 MB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/1. Section Overview.mp4 7.8 MB
- 13. Data Engineering/1. Data Engineering Introduction.mp4 7.7 MB
- 3. Machine Learning and Data Science Framework/1. Section Overview.mp4 7.7 MB
- 20. Where To Go From Here/1. Thank You.mp4 7.6 MB
- 13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp4 7.2 MB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp4 7.0 MB
- 3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 6.9 MB
- 15. Storytelling + Communication How To Present Your Projects/7. Storytelling.mp4 6.8 MB
- 5. Data Science Environment Setup/3. What is Conda.mp4 6.8 MB
- 9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp4 6.8 MB
- 9. Scikit-learn Creating Machine Learning Models/20. Quick Tip How ML Algorithms Work.mp4 6.3 MB
- 6. Pandas Data Analysis/1. Section Overview.mp4 6.1 MB
- 16. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 6.0 MB
- 15. Storytelling + Communication How To Present Your Projects/1. Section Overview.mp4 6.0 MB
- 11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.mp4 5.6 MB
- 8. Matplotlib Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 5.2 MB
- 3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 4.8 MB
- 4. The 2 Paths/1. The 2 Paths.mp4 4.8 MB
- 8. Matplotlib Plotting and Data Visualization/1. Section Overview.mp4 4.8 MB
- 5. Data Science Environment Setup/1. Section Overview.mp4 3.1 MB
- 13. Data Engineering/12. Apache Spark and Apache Flink.mp4 3.1 MB
- 2. Machine Learning 101/9. Section Review.mp4 2.7 MB
- 20. Where To Go From Here/6. LinkedIn Endorsements.html 275.9 KB
- 20. Where To Go From Here/5. ZTM Events Every Month.html 273.3 KB
- 20. Where To Go From Here/4. Learning Guideline.html 272.3 KB
- 20. Where To Go From Here/3. Become An Alumni.html 271.4 KB
- 20. Where To Go From Here/2. Review This Course!.html 270.4 KB
- 19. Bonus Learn Advanced Statistics and Mathematics/1. Statistics and Mathematics.html 269.0 KB
- 18. Learn Python Part 2/1. Watch Python Basics 2 Section.html 268.2 KB
- 17. Learn Python/1. Watch Learn Python Section.html 267.4 KB
- 16. Career Advice + Extra Bits/8. Coding Challenges.html 266.5 KB
- 16. Career Advice + Extra Bits/5. Quick Note Upcoming Videos.html 263.2 KB
- 16. Career Advice + Extra Bits/4. Learning Guideline.html 262.1 KB
- 16. Career Advice + Extra Bits/2. Quick Note Upcoming Video.html 260.4 KB
- 16. Career Advice + Extra Bits/1. Endorsements On LinkedIn.html 260.3 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/44. Finishing Dog Vision Where to next.html 255.0 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/24. Optional How machines learn and what's going on behind the scenes.html 234.6 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/3. Setting Up With Google.html 212.3 KB
- 13. Data Engineering/10. Optional Learn SQL.html 206.3 KB
- 13. Data Engineering/8. Quick Note Upcoming Video.html 204.5 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Challenge What's wrong with splitting data after filling it.html 191.4 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Downloading the data for the next two projects.html 180.8 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/18. Quick Note Confusion Matrix Labels.html 171.7 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/5. Note Code update for next video.html 159.9 KB
- 9. Scikit-learn Creating Machine Learning Models/52. Scikit-Learn Practice.html 154.3 KB
- 10. Supervised Learning Classification + Regression/1. Milestone Projects!.html 153.9 KB
- 9. Scikit-learn Creating Machine Learning Models/46. Note Metric Comparison Improvement.html 148.6 KB
- 9. Scikit-learn Creating Machine Learning Models/39. Machine Learning Model Evaluation.html 146.3 KB
- 9. Scikit-learn Creating Machine Learning Models/32. Reading Extension ROC Curve + AUC.html 134.2 KB
- 9. Scikit-learn Creating Machine Learning Models/19. Quick Note Decision Trees.html 120.3 KB
- 9. Scikit-learn Creating Machine Learning Models/15. Note Correction in the upcoming video.html 118.1 KB
- 9. Scikit-learn Creating Machine Learning Models/14. Extension Feature Scaling.html 118.0 KB
- 9. Scikit-learn Creating Machine Learning Models/12. Note Update to next video (OneHotEncoder can handle NaNNone values).html 114.8 KB
- 9. Scikit-learn Creating Machine Learning Models/5. Quick Note Upcoming Videos.html 107.5 KB
- 9. Scikit-learn Creating Machine Learning Models/3. Quick Note Upcoming Video.html 104.9 KB
- 8. Matplotlib Plotting and Data Visualization/20. Assignment Matplotlib Practice.html 103.7 KB
- 8. Matplotlib Plotting and Data Visualization/10. Quick Note Regular Expressions.html 92.6 KB
- 7. NumPy/3.1. Quick Note Correction In Next Video.jpg 87.2 KB
- 7. NumPy/18. Assignment NumPy Practice.html 83.6 KB
- 7. NumPy/19. Optional Extra NumPy resources.html 83.4 KB
- 7. NumPy/7. Endorsements On LinkedIn.html 72.3 KB
- 7. NumPy/3. Quick Note Correction In Next Video.html 68.4 KB
- 6. Pandas Data Analysis/16. Implement a New Life System.html 64.5 KB
- 6. Pandas Data Analysis/14. Assignment Pandas Practice.html 64.4 KB
- 6. Pandas Data Analysis/9. Quick Note Upcoming Video.html 59.7 KB
- 6. Pandas Data Analysis/5.2. Data from URLs.jpg 59.5 KB
- 6. Pandas Data Analysis/6. Quick Note Upcoming Videos.html 56.7 KB
- 6. Pandas Data Analysis/5. Data from URLs.html 54.9 KB
- 6. Pandas Data Analysis/2. Downloading Workbooks and Assignments.html 51.6 KB
- 5. Data Science Environment Setup/14. Course Check-In.html 49.1 KB
- 5. Data Science Environment Setup/10. Sharing your Conda Environment.html 47.9 KB
- 5. Data Science Environment Setup/9. Linux Environment Setup.html 45.1 KB
- 9. Scikit-learn Creating Machine Learning Models/40. NEW Evaluating A Model With Cross Validation and Scoring Parameter.srt 40.5 KB
- 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.srt 38.6 KB
- 5. Data Science Environment Setup/8. Windows Environment Setup 2.srt 37.4 KB
- 9. Scikit-learn Creating Machine Learning Models/43. Tuning Hyperparameters.srt 36.5 KB
- 4. The 2 Paths/2. Python + Machine Learning Monthly.html 36.4 KB
- 3. Machine Learning and Data Science Framework/16. Unlimited Updates.html 33.9 KB
- 3. Machine Learning and Data Science Framework/15. Optional Elements of AI.html 33.7 KB
- 9. Scikit-learn Creating Machine Learning Models/17. NEW Choosing The Right Model For Your Data.srt 32.3 KB
- 3. Machine Learning and Data Science Framework/12. Overfitting and Underfitting Definitions.html 31.9 KB
- 9. Scikit-learn Creating Machine Learning Models/50. Putting It All Together.srt 31.4 KB
- 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.srt 30.2 KB
- 5. Data Science Environment Setup/5. Mac Environment Setup.srt 28.8 KB
- 9. Scikit-learn Creating Machine Learning Models/16. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 28.5 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/32. Training Your Deep Neural Network.srt 28.0 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 2.srt 27.6 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Feature Engineering.srt 26.5 KB
- 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.srt 25.9 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/22. Finding The Most Important Features.srt 25.9 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Turning Data Into Numbers.srt 25.6 KB
- 5. Data Science Environment Setup/6. Mac Environment Setup 2.srt 25.4 KB
- 5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 2.srt 25.3 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/41. Making Predictions On Test Images.srt 24.5 KB
- 9. Scikit-learn Creating Machine Learning Models/34. NEW Evaluating A Classification Model 5 (Confusion Matrix).srt 24.4 KB
- 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Machine Learning Model 2 (Cross Validation).srt 24.0 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21. Turning Data Into Batches 2.srt 24.0 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data.srt 23.8 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/43. Making Predictions On Our Images.srt 23.4 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/2. Deep Learning and Unstructured Data.srt 23.4 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/40. Training Model On Full Dataset.srt 23.3 KB
- 7. NumPy/4. NumPy DataTypes and Attributes.srt 23.0 KB
- 9. Scikit-learn Creating Machine Learning Models/41. NEW Evaluating A Model With Scikit-learn Functions.srt 22.6 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/37. Visualizing And Evaluate Model Predictions 2.srt 22.3 KB
- 6. Pandas Data Analysis/11. Manipulating Data.srt 22.0 KB
- 9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Pandas.srt 21.9 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictions.srt 21.9 KB
- 6. Pandas Data Analysis/10. Selecting and Viewing Data with Pandas Part 2.srt 21.8 KB
- 9. Scikit-learn Creating Machine Learning Models/21. Choosing The Right Model For Your Data 3 (Classification).srt 21.7 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/10. Finding Patterns 3.srt 21.4 KB
- 9. Scikit-learn Creating Machine Learning Models/45. Tuning Hyperparameters 3.srt 21.4 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Preproccessing Our Data.srt 21.2 KB
- 6. Pandas Data Analysis/4. Series, Data Frames and CSVs.srt 21.0 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/35. Transform Predictions To Text.srt 20.9 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/36. Visualizing Model Predictions.srt 20.8 KB
- 7. NumPy/14. Exercise Nut Butter Store Sales.srt 20.8 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/39. Saving And Loading A Trained Model.srt 20.0 KB
- 7. NumPy/9. Manipulating Arrays.srt 19.9 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.srt 19.9 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/42. Submitting Model to Kaggle.srt 19.8 KB
- 8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.srt 19.6 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Numerical Values.srt 19.4 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25. Building A Deep Learning Model.srt 19.3 KB
- 9. Scikit-learn Creating Machine Learning Models/44. Tuning Hyperparameters 2.srt 19.2 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/14. TuningImproving Our Model.srt 19.2 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 2.srt 19.1 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/15. Custom Evaluation Function.srt 19.1 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Project Environment Setup.srt 18.8 KB
- 2. Machine Learning 101/10. Let's Have Some Fun (+ Free Resources).html 18.5 KB
- 7. NumPy/13. Dot Product vs Element Wise.srt 18.4 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14. Loading Our Data Labels.srt 18.4 KB
- 8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.srt 18.1 KB
- 9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Classification Model 4 (Confusion Matrix).srt 18.1 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters.srt 18.1 KB
- 9. Scikit-learn Creating Machine Learning Models/51. Putting It All Together 2.srt 17.8 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.srt 17.8 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/22. Visualizing Our Data.srt 17.7 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Reducing Data.srt 17.6 KB
- 8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.srt 17.5 KB
- 6. Pandas Data Analysis/12. Manipulating Data 2.srt 17.5 KB
- 9. Scikit-learn Creating Machine Learning Models/42. Improving A Machine Learning Model.srt 17.4 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/15. Preparing The Images.srt 17.4 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/21. Feature Importance.srt 17.2 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/9. Importing TensorFlow 2.srt 17.1 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/16. Turning Data Labels Into Numbers.srt 17.1 KB
- 6. Pandas Data Analysis/13. Manipulating Data 3.srt 16.8 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/12. Choosing The Right Models.srt 16.8 KB
- 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.srt 16.7 KB
- 6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas.srt 16.5 KB
- 3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.srt 16.5 KB
- 8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.srt 16.3 KB
- 9. Scikit-learn Creating Machine Learning Models/26. NEW Evaluating A Machine Learning Model (Score) Part 1.srt 16.2 KB
- 9. Scikit-learn Creating Machine Learning Models/18. NEW Choosing The Right Model For Your Data 2 (Regression).srt 16.2 KB
- 9. Scikit-learn Creating Machine Learning Models/36. NEW Evaluating A Regression Model 1 (R2 Score).srt 16.0 KB
- 8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.srt 16.0 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/23. Reviewing The Project.srt 16.0 KB
- 8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.srt 15.9 KB
- 6. Pandas Data Analysis/7. Describing Data with Pandas.srt 15.9 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model.srt 15.7 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Splitting Data.srt 15.7 KB
- 2. Machine Learning 101/7. Are You Getting It Yet.html 15.6 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/19. Preprocess Images 2.srt 15.6 KB
- 8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.srt 15.6 KB
- 8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.srt 15.5 KB
- 9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Classification Model 6 (Classification Report).srt 15.4 KB
- 7. NumPy/8. Viewing Arrays and Matrices.srt 15.4 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/6. Getting Our Tools Ready.srt 15.3 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. RandomizedSearchCV.srt 15.1 KB
- 3. Machine Learning and Data Science Framework/11. Modelling - Comparison.srt 15.0 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18. Preprocess Images.srt 15.0 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/26. Building A Deep Learning Model 2.srt 14.9 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns.srt 14.7 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/11. Using A GPU.srt 14.6 KB
- 7. NumPy/5. Creating NumPy Arrays.srt 14.6 KB
- 9. Scikit-learn Creating Machine Learning Models/25. NEW Making Predictions With Our Model (Regression).srt 14.4 KB
- 13. Data Engineering/9. Optional OLTP Databases.srt 14.3 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/11. Preparing Our Data For Machine Learning.srt 14.3 KB
- 8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.srt 14.2 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28. Building A Deep Learning Model 4.srt 14.2 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Step 1~4 Framework Setup.srt 14.2 KB
- 9. Scikit-learn Creating Machine Learning Models/23. Making Predictions With Our Model.srt 14.1 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/21. Evaluating Our Model 3.srt 13.9 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27. Building A Deep Learning Model 3.srt 13.9 KB
- 9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 2 (ROC Curve).srt 13.8 KB
- 8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.srt 13.7 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Improving Hyperparameters.srt 13.6 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/38. Visualizing And Evaluate Model Predictions 3.srt 13.6 KB
- 9. Scikit-learn Creating Machine Learning Models/38. NEW Evaluating A Regression Model 3 (MSE).srt 13.6 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/20. Turning Data Into Batches.srt 13.6 KB
- 9. Scikit-learn Creating Machine Learning Models/12.1. Note Update to next video (OneHotEncoder can handle NaNNone values).jpg 13.6 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/7. Exploring Our Data.srt 13.3 KB
- 7. NumPy/10. Manipulating Arrays 2.srt 13.3 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Filling Missing Categorical Values.srt 13.3 KB
- 9. Scikit-learn Creating Machine Learning Models/24. predict() vs predict_proba().srt 13.2 KB
- 5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.srt 13.1 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/30. Evaluating Our Model.srt 13.0 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17. Creating Our Own Validation Set.srt 13.0 KB
- 9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.srt 12.9 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/20. Making Predictions.srt 12.8 KB
- 8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.srt 12.4 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.srt 12.1 KB
- 7. NumPy/17. Turn Images Into NumPy Arrays.srt 11.9 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/33. Evaluating Performance With TensorBoard.srt 11.7 KB
- 8. Matplotlib Plotting and Data Visualization/9. Plotting From Pandas DataFrames.srt 11.7 KB
- 9. Scikit-learn Creating Machine Learning Models/48. Saving And Loading A Model.srt 11.6 KB
- 9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 3 (ROC Curve).srt 11.3 KB
- 9. Scikit-learn Creating Machine Learning Models/27. NEW Evaluating A Machine Learning Model (Score) Part 2.srt 11.3 KB
- 9. Scikit-learn Creating Machine Learning Models/22. Fitting A Model To The Data.srt 11.1 KB
- 7. NumPy/6. NumPy Random Seed.srt 11.0 KB
- 8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.srt 10.9 KB
- 7. NumPy/16. Sorting Arrays.srt 10.9 KB
- 9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.srt 10.9 KB
- 7. NumPy/12. Reshape and Transpose.srt 10.7 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Fitting A Machine Learning Model.srt 10.6 KB
- 9. Scikit-learn Creating Machine Learning Models/49. Saving And Loading A Model 2.srt 10.4 KB
- 9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.srt 10.4 KB
- 15. Storytelling + Communication How To Present Your Projects/5. Weekend Project Principle.srt 10.3 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4. Setting Up Google Colab.srt 10.3 KB
- 1. Introduction/2. Course Outline.srt 10.2 KB
- 6. Pandas Data Analysis/15. How To Download The Course Assignments.srt 10.2 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6. Uploading Project Data.srt 10.2 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/13. Experimenting With Machine Learning Models.srt 10.2 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/17. Tuning Hyperparameters 3.srt 10.1 KB
- 2. Machine Learning 101/1. What Is Machine Learning.srt 10.1 KB
- 1. Introduction/8. Asking Questions + Getting Help.html 10.1 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/13. Optional Reloading Colab Notebook.srt 9.9 KB
- 9. Scikit-learn Creating Machine Learning Models/37. NEW Evaluating A Regression Model 2 (MAE).srt 9.9 KB
- 13. Data Engineering/7. Types of Databases.srt 9.7 KB
- 8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.srt 9.3 KB
- 2. Machine Learning 101/3. Exercise Machine Learning Playground.srt 9.3 KB
- 5. Data Science Environment Setup/7. Windows Environment Setup.srt 8.9 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/20. Evaluating Our Model 2.srt 8.7 KB
- 7. NumPy/2. NumPy Introduction.srt 8.7 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Exploring Our Data 2.srt 8.6 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23. Preparing Our Inputs and Outputs.srt 8.6 KB
- 13. Data Engineering/2. What Is Data.srt 8.4 KB
- 2. Machine Learning 101/4. How Did We Get Here.srt 8.3 KB
- 3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.srt 8.2 KB
- 1. Introduction/7. Set Your Learning Streak Goal.html 8.0 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.srt 8.0 KB
- 3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.srt 7.8 KB
- 3. Machine Learning and Data Science Framework/7. Features In Data.srt 7.7 KB
- 6. Pandas Data Analysis/3. Pandas Introduction.srt 7.6 KB
- 9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.srt 7.5 KB
- 3. Machine Learning and Data Science Framework/5. Types of Data.srt 7.3 KB
- 2. Machine Learning 101/2. AIMachine LearningData Science.srt 7.2 KB
- 1. Introduction/1. Complete A.I. Machine Learning and Data Science Zero to Mastery.srt 7.2 KB
- 13. Data Engineering/4. What is A Data Engineer 2.srt 7.2 KB
- 3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.srt 7.1 KB
- 1. Introduction/6. ZTM Plugin + Understanding Your Video Player.html 7.0 KB
- 5. Data Science Environment Setup/4. Conda Environments.srt 7.0 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5. Google Colab Workspace.srt 7.0 KB
- 2. Machine Learning 101/8. What Is Machine Learning Round 2.srt 7.0 KB
- 8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.srt 6.9 KB
- 8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.srt 6.9 KB
- 9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 1 (Accuracy).srt 6.8 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/29. Summarizing Our Model.srt 6.7 KB
- 3. Machine Learning and Data Science Framework/14. Tools We Will Use.srt 6.7 KB
- 9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.srt 6.6 KB
- 2. Machine Learning 101/6. Types of Machine Learning.srt 6.5 KB
- 2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.srt 6.4 KB
- 15. Storytelling + Communication How To Present Your Projects/4. Communicating With Co-Workers.srt 6.3 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31. Preventing Overfitting.srt 6.2 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/7. Setting Up Our Data.srt 6.1 KB
- 13. Data Engineering/13. Kafka and Stream Processing.srt 6.1 KB
- 1. Introduction/5. Your First Day.srt 6.0 KB
- 13. Data Engineering/5. What is a Data Engineer 3.srt 5.9 KB
- 3. Machine Learning and Data Science Framework/10. Modelling - Tuning.srt 5.8 KB
- 3. Machine Learning and Data Science Framework/13. Experimentation.srt 5.8 KB
- 7. NumPy/15. Comparison Operators.srt 5.8 KB
- 13. Data Engineering/11. Hadoop, HDFS and MapReduce.srt 5.7 KB
- 15. Storytelling + Communication How To Present Your Projects/2. Communicating Your Work.srt 5.5 KB
- 1. Introduction/4. Course Resources.html 5.3 KB
- 3. Machine Learning and Data Science Framework/1. Section Overview.srt 5.2 KB
- 3. Machine Learning and Data Science Framework/6. Types of Evaluation.srt 5.2 KB
- 15. Storytelling + Communication How To Present Your Projects/3. Communicating With Managers.srt 5.2 KB
- 15. Storytelling + Communication How To Present Your Projects/6. Communicating With Outside World.srt 5.2 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10. Optional TensorFlow 2.0 Default Issue.srt 5.1 KB
- 4. The 2 Paths/1. The 2 Paths.srt 5.0 KB
- 5. Data Science Environment Setup/2. Introducing Our Tools.srt 5.0 KB
- 13. Data Engineering/1. Data Engineering Introduction.srt 4.9 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/24. Exercise Imposter Syndrome.srt 4.8 KB
- 9. Scikit-learn Creating Machine Learning Models/1. Section Overview.srt 4.7 KB
- 15. Storytelling + Communication How To Present Your Projects/7. Storytelling.srt 4.5 KB
- 1. Introduction/3. Exercise Meet Your Classmates and Instructor.html 4.5 KB
- 13. Data Engineering/6. What is a Data Engineer 4.srt 4.4 KB
- 20. Where To Go From Here/1. Thank You.srt 4.3 KB
- 3. Machine Learning and Data Science Framework/2. Introducing Our Framework.srt 4.0 KB
- 7. NumPy/1. Section Overview.srt 3.8 KB
- 6. Pandas Data Analysis/1. Section Overview.srt 3.8 KB
- 5. Data Science Environment Setup/3. What is Conda.srt 3.7 KB
- 16. Career Advice + Extra Bits/7. JTS Start With Why.srt 3.5 KB
- 11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.srt 3.4 KB
- 15. Storytelling + Communication How To Present Your Projects/1. Section Overview.srt 3.3 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/1. Section Overview.srt 3.2 KB
- 8. Matplotlib Plotting and Data Visualization/1. Section Overview.srt 3.0 KB
- 9. Scikit-learn Creating Machine Learning Models/47. Quick Tip Correlation Analysis.srt 3.0 KB
- 13. Data Engineering/12. Apache Spark and Apache Flink.srt 2.8 KB
- 2. Machine Learning 101/9. Section Review.srt 2.7 KB
- 14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/8. Setting Up Our Data 2.srt 2.5 KB
- 16. Career Advice + Extra Bits/6. JTS Learn to Learn.srt 2.3 KB
- 8. Matplotlib Plotting and Data Visualization/8. Quick Tip Data Visualizations.srt 2.3 KB
- 9. Scikit-learn Creating Machine Learning Models/20. Quick Tip How ML Algorithms Work.srt 2.2 KB
- 5. Data Science Environment Setup/1. Section Overview.srt 1.9 KB
- 12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.srt 1.8 KB
Download Torrent
Related Resources
Copyright Infringement
If the content above is not authorized, please contact us via activebusinesscommunication[AT]gmail.com. Remember to include the full url in your complaint.