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Feature Engineering in Pandas for Deep Learning in Keras (2.5)
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Applications of Deep Neural Networks for TensorFlow and Keras
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- 1 Deep Learning Course with Python, Keras and TensorFlow with Applications of Deep Neural Networks.
- 2 Applications of Deep Neural Networks Course Overview (1.1, Fall 2021)
- 3 Introduction to Python for Deep Learning (1.2)
- 4 Python Lists, Dictionaries, Sets & JSON (1.3)
- 5 Python File Handling for Deep Learning (1.4)
- 6 Python Functions, Lambdas, and Map/Reduce (1.5)
- 7 2021, Installing TensorFlow 2.5, Keras, & Python 3.9 in Mac OSX M1
- 8 Installing TensorFlow/Keras CPU/GPU w/CONDA (July, 2020)
- 9 2021, Installing TensorFlow 2.4, Keras, & Python 3.8 in Mac OSX Intel
- 10 Using Google CoLab for the Course Applications of Deep Neural Networks
- 11 How to Submit Assignment for Application of Deep Learning (2020 update)
- 12 Introduction to Pandas for Deep Learning (2.1)
- 13 Encoding Categorical Values in Pandas for Keras (2.2)
- 14 Grouping, Sorting, and Shuffling in Python Pandas (2.3)
- 15 Using Apply and Map in Pandas for Keras (2.4)
- 16 Feature Engineering in Pandas for Deep Learning in Keras (2.5)
- 17 Deep Learning and Neural Network Introduction with Keras (3.1)
- 18 Introduction to Tensorflow & Keras for Deep Learning with Python (3.2)
- 19 Saving and Loading a Keras Neural Network (3.3)
- 20 Early Stopping in Keras to Prevent Overfitting (3.4)
- 21 Extracting Keras Weights and Manual Neural Network Calculation (3.5)
- 22 Encoding a Feature Vector for Keras Deep Learning (4.1)
- 23 Keras Multiclass Classification for Deep Neural Networks with ROC and AUC (4.2)
- 24 Keras Regression for Deep Neural Networks with RMSE (4.3)
- 25 Backpropagation, Nesterov Momentum, and ADAM Training (4.4)
- 26 Neural Network RMSE and Log Loss Error Calculation from Scratch (4.5)
- 27 Introduction to Regularization: Ridge and Lasso (5.1)
- 28 Using K-Fold Cross Validation with Keras (5.2)
- 29 Using L1 and L2 Regularization with Keras to Decrease Overfitting (5.3)
- 30 Drop Out for Keras to Decrease Overfitting (5.4)
- 31 Bootstrapping and Benchmarking Hyperparameters (5.5)
- 32 Image Processing in Python for Keras Neural Networks (6.1)
- 33 Keras Convolutional Neural Neural Networks for MNIST and Fashion MNIST (6.2)
- 34 Implementing a ResNet in Keras (6.3)
- 35 Using your own Images with Keras (6.4)
- 36 Recognizing Multiple Images with YOLO Darknet (6.5)
- 37 Introduction to Generative Adversarial Neural Networks (GANs) for Image and Data Generation (7.1)
- 38 Generating Faces with a Generative Adversarial Networks (GAN) in Keras/Tensorflow 2.0 (7.2)
- 39 Face Generation with NVIDIA StyleGAN2-ADA PyTorch and Python 3 (7.3)
- 40 GANS for Semi-Supervised Learning in Keras (7.4)
- 41 Some New Topics in the area of Generative Adversarial Network (GAN) Research (7.5)
- 42 Introduction to Kaggle (8.1)
- 43 Building Ensembles with Scikit-Learn and Keras (8.2)
- 44 How Should you Architect Your Keras Neural Network: Hyperparameters (8.3)
- 45 Bayesian Hyperparameter Optimization for Keras (8.4)
- 46 Spring 2020 Kaggle Competition for Applications of Deep Learning (8.5)
- 47 Introduction to Keras Transfer Learning (9.1)
- 48 Popular Pretrained Neural Networks for Keras (9.2)
- 49 Transfer Learning for Computer Vision and Keras (9.3)
- 50 Transfer Learning for Languages and Keras (9.4)
- 51 Transfer Learning for Keras Feature Engineering (9.5)
- 52 Time Series Data Encoding for Deep Learning, TensorFlow and Keras (10.1)
- 53 Programming LSTM with Keras and TensorFlow (10.2)
- 54 Text Generation with Keras and TensorFlow (10.3)
- 55 Image Captioning with Keras and TensorFlow (10.4)
- 56 Temporal Convolutional Neural Networks in Keras (10.5)
- 57 Getting Started with Spacy in Python (11.1)
- 58 Word2Vec and Text Classification (11.2)
- 59 What are Embedding Layers in Keras (11.3)
- 60 Natural Language Processing with Spacy and Keras (11.4)
- 61 Learning English from Scratch with Keras and TensorFlow (11.5)
- 62 Introduction to the OpenAI Gym (12.1)
- 63 Introduction to Q-Learning for Game Play (12.2)
- 64 Keras Q-Learning in the OpenAI Gym (12.3)
- 65 Atari Games with Keras TF-Agents (12.4)
- 66 Reinforcement Learning for Non-Games TF-Agents (12.5)
- 67 Flask and Deep Learning Keras/TensorFlow Web Services (13.1)
- 68 Resuming Training and Checkpoints in Python TensorFlow Keras (13.2)
- 69 Using a Keras Deep Neural Network with a Web Application (13.3)
- 70 When to Retrain Your Neural Network (13.4)
- 71 TensorFlow Lite for IOS Development (13.5)
- 72 Automated Machine Learning (AutoML) for Keras and TensorFlow (14.1)
- 73 Using Denoising AutoEncoders in Keras (14.2)
- 74 Anomaly Detection in Keras with AutoEncoders (14.3)
- 75 Training an Intrusion Detection System with Keras and KDD99 (14.4)
- 76 New Deep Learning Technology for Course (14.5)
