01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/004 Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11.7 MB
03 Momentum and adaptive learning rates/010 Constant learning rate vs. RMSProp in Code.mp4 11.5 MB
09 Project Facial Expression Recognition/026 The class imbalance problem.mp4 10.6 MB
07 GPU Speedup Homework and Other Misc Topics/022 Theano vs. TensorFlow.mp4 9.6 MB
01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/003 How to Succeed in this Course.mp4 9.2 MB
04 Choosing Hyperparameters/013 Random Search in Code.mp4 8.3 MB
07 GPU Speedup Homework and Other Misc Topics/021 How to Improve your Theano and Tensorflow Skills.mp4 7.7 MB
08 Modern Regularization Techniques/024 Dropout Intuition.mp4 6.4 MB
01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/002 Where does this course fit into your deep learning studies.mp4 6.3 MB
02 Gradient Descent Full vs Batch vs Stochastic/005 What are full batch and stochastic gradient descent.mp4 6.1 MB
04 Choosing Hyperparameters/011 Hyperparameter Optimization Cross-validation Grid Search and Random Search.mp4 5.8 MB
07 GPU Speedup Homework and Other Misc Topics/019 Can Big Data be used to Speed Up Backpropagation.mp4 5.5 MB
03 Momentum and adaptive learning rates/009 Variable and adaptive learning rates.mp4 5.3 MB
01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/001 Outline - what did you learn previously and what will you learn in this course.mp4 4.9 MB
07 GPU Speedup Homework and Other Misc Topics/020 Exercises and Concepts Still to be Covered.mp4 4.7 MB
03 Momentum and adaptive learning rates/007 Momentum.mp4 3.3 MB