ile:README.md file:772462_d385.jpg file:671576_a272_42.jpg file:713104_d4cb.jpg file:033 How to Code by Yourself part 2.mp4 file:031 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 file:030 Manually Choosing Learning Rate and Regularization Penalty.mp4 file:029 Class-Based ANN in TensorFlow.mp4 file:027 Utilities walkthrough.mp4 file:026 The class imbalance problem.mp4 file:025 Facial Expression Recognition Problem Description.mp4 file:024 Dropout Intuition.mp4 file:022 Theano vs. TensorFlow.mp4 file:021 How to Improve your Theano and Tensorflow Skills.mp4 file:020 Exercises and Concepts Still to be Covered.mp4 file:019 Can Big Data be used to Speed Up Backpropagation.mp4 file:018 Setting up a GPU Instance on Amazon Web Services.mp4 file:017 Building a neural network in TensorFlow.mp4 file:016 TensorFlow Basics Variables Functions Expressions Optimization.mp4 file:013 Random Search in Code.mp4 file:011 Hyperparameter Optimization Cross-validation Grid Search and Random Search.mp4 file:010 Constant learning rate vs. RMSProp in Code.mp4 file:009 Variable and adaptive learning rates.mp4 file:008 Code for training a neural network using momentum.mp4 file:007 Momentum.mp4 file:006 Full vs Batch vs Stochastic Gradient Descent in code.mp4 file:005 What are full batch and stochastic gradient descent.mp4 file:004 Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 file:003 How to Succeed in this Course.mp4 file:002 Where does this course fit into your deep learning studies.mp4 file:001 Outline - what did you learn previously and what will you learn in this course.mp4 file:7. EXTRA LSTM Variations.srt file:6. Practical intuition.srt file:5. LSTMs.srt file:4. The Vanishing Gradient Problem.srt file:3. The idea behind Recurrent Neural Networks.srt file:2. Plan of attack.srt

ile:README.md file:Python-For-Computer-Vision-With-OpenCV-And-Deep-Learning.jpg file:Deep-Learning-and-Computer-Vision-A-Z™-OpenCV-SSD-GANs.jpg file:1281492_28d8_3.jpg file:807904_7108.jpg file:a78aaf7c95ff28eebec9e85074a4dacafdd5ca1a.jpg file:5. Capstone Part Four - Bringing it all together.srt file:4. Capstone Part Three - Counting and ConvexHull.srt file:3. Capstone Part Two - Segmentation.srt file:2. Capstone Part One - Variables and Background function.srt file:1. Introduction to CapStone Project.srt file:9. Keras Basics.srt file:8. Gradient Descent and Back Propagation.srt file:7. Cost Functions.srt file:6. Understanding a Neural Network.srt file:8. Tracking APIs with OpenCV.srt file:7.5 KCF Tracker.html file:7.4 BOOSTING Tracker Info.html file:7. Overview of various Tracking API Methods.srt file:6. MeanShift and CamShift Tracking with OpenCV.srt

ile:README.md file:Deep-Reinforcement-Learning-2.0.jpg file:Cutting-Edge-AI-Deep.jpg file:1080408_2645_3.jpg file:1153742_e649.jpg file:1. YOUR SPECIAL BONUS.html file:5. Action Selection Policies.vtt file:4. Experience Replay.vtt file:3. Deep Q-Learning Intuition - Step 2.vtt file:1. Plan of Attack.vtt file:9. Temporal Difference.vtt file:7. Living Penalty.vtt file:6. Policy vs Plan.vtt file:5. Markov Decision Process.vtt file:8. Backpropagation.vtt file:7. Stochastic Gradient Descent.vtt file:5. How do Neural Networks Learn.vtt file:3. The Activation Function.vtt