Computer Vision Projects with Python 3 [Video]
File List
- 4.Deep Learning Image Classification with TensorFlow/17.Retraining with Our Own Images.mp4 52.0 MB
- 1.Introduction and Tool Setup/03.Installing Additional Libraries.mp4 47.2 MB
- 4.Deep Learning Image Classification with TensorFlow/16.Using a Pre-Trained Model (Inception) for Image Classification.mp4 44.5 MB
- 3.Facial Feature Tracking and Classification with dlib/12.Example One – Finding 68 Facial Landmarks in Images.mp4 40.1 MB
- 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/08.Introducing TensorFlow with Digit Classification.mp4 39.1 MB
- 3.Facial Feature Tracking and Classification with dlib/14.Example Three – Facial Recognition.mp4 37.6 MB
- 1.Introduction and Tool Setup/04.Exploring the Jupyter Notebook.mp4 34.7 MB
- 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/07.Applying the Support Vector Machine to New Data.mp4 31.5 MB
- 3.Facial Feature Tracking and Classification with dlib/10.Introducing dlib.mp4 26.9 MB
- 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/05.Acquiring and Processing MNIST Digit Data.mp4 24.6 MB
- 4.Deep Learning Image Classification with TensorFlow/15.A Deeper Introduction to TensorFlow.mp4 22.2 MB
- 1.Introduction and Tool Setup/02.Downloading and Installing Python 3_Anaconda.mp4 22.1 MB
- 3.Facial Feature Tracking and Classification with dlib/13.Example Two – Faces in Videos.mp4 19.0 MB
- 4.Deep Learning Image Classification with TensorFlow/18.Speeding Up Computations with GPUs.mp4 17.5 MB
- 1.Introduction and Tool Setup/01.The Course Overview.mp4 13.4 MB
- 3.Facial Feature Tracking and Classification with dlib/11.What Are Facial Landmarks.mp4 12.8 MB
- 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/09.Evaluating the Results.mp4 12.7 MB
- 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/06.Creating and Training a Support Vector Machine.mp4 7.9 MB
- Exercise Files/code_33881.zip 4.1 MB
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