Learn Deep Learning with Python, Keras and TensorFlow, WashU Applications of Deep Neural Networks

Applications of Deep Neural Networks Course Overview (1.1, Spring 2023)

Introduction to Python for Deep Learning (1.2)

Python Lists, Dictionaries, Sets & JSON (1.3)

Python File Handling for Deep Learning (1.4)

Python Functions, Lambdas, and Map/Reduce (1.5)

Installing TensorFlow/Keras CPU/GPU w/CONDA (July, 2020)

How to Install Tensorflow Keras GPU for Mac M1/M2 with Conda

2021, Installing TensorFlow 2.4, Keras, & Python 3.8 in Mac OSX Intel

Using Google CoLab for the Course Applications of Deep Neural Networks

How to Submit Assignment for Application of Deep Learning (2020 update)

Introduction to Pandas for Deep Learning (2.1)

Encoding Categorical Values in Pandas for Keras (2.2)

Grouping, Sorting, and Shuffling in Python Pandas (2.3)

Using Apply and Map in Pandas for Keras (2.4)

Feature Engineering in Pandas for Deep Learning in Keras (2.5)

Deep Learning and Neural Network Introduction with Keras (3.1)

Introduction to Tensorflow & Keras for Deep Learning with Python (3.2)

Saving and Loading a Keras Neural Network (3.3)

Early Stopping in Keras to Prevent Overfitting (3.4)

Extracting Keras Weights and Manual Neural Network Calculation (3.5)

Encoding a Feature Vector for Keras Deep Learning (4.1)

Keras Multiclass Classification for Deep Neural Networks with ROC and AUC (4.2)

Keras Regression for Deep Neural Networks with RMSE (4.3)

Backpropagation, Nesterov Momentum, and ADAM Training (4.4)

Neural Network RMSE and Log Loss Error Calculation from Scratch (4.5)

Introduction to Regularization: Ridge and Lasso (5.1)

Using K-Fold Cross Validation with Keras (5.2)

Using L1 and L2 Regularization with Keras to Decrease Overfitting (5.3)

Drop Out for Keras to Decrease Overfitting (5.4)

Bootstrapping and Benchmarking Hyperparameters (5.5)

Image Processing in Python for Keras Neural Networks (6.1)

Keras Convolutional Neural Neural Networks for Regression and Classification (6.2)

Using Pretrained Neural Networks with Keras (6.3)

Looking at Keras Generators and Image Augmentation (6.4)

Recognizing Multiple Images with YOLOv5 (6.5)

Introduction to GANS for Image and Data Generation (7.1)

Train StyleGAN with your Own Images (7.2)

Exploring the StyleGAN Latent Vector (7.3)

GANs to Enhance Old Photographs Deoldify (7.4)

GANs for Tabular Synthetic Data Generation (7.5)

Introduction to Kaggle (8.1)

Building Ensembles with Scikit-Learn and Keras (8.2)

How Should you Architect Your Keras Neural Network: Hyperparameters (8.3)

Bayesian Hyperparameter Optimization for Keras (8.4)

Introduction to Keras Transfer Learning (9.1)

Keras Transfer Learning for Computer Vision (9.2)

Keras Transfer Learning for NLP (9.3)

Detect Facial Features for StyleGAN Cropping (9.4)

Transfer Learning for Keras Image Style Transfer (9.5)

Time Series Data Encoding for Deep Learning, TensorFlow and Keras (10.1)

Programming LSTM with Keras and TensorFlow (10.2)

Text Generation with Keras and TensorFlow (10.3)

Introduction to Neural Network Transformers (10.4)

Neural Transformer Encoders for Timeseries Data in Keras (10.5)

Introduction to Hugging Face Classifiers (11.1)

Hugging Face Tokenizers (11.2)

Hugging Face Data Sets (11.3)

Hugging Face Train a Model (11.4)

What are Embedding Layers in Keras (11.5)

Introduction to the OpenAI Gym (12.1)

Introduction to Q-Learning for Game Play (12.2)

Keras Q-Learning in the OpenAI Gym (12.3)

Atari Games with Keras TF-Agents (12.4)

Reinforcement Learning for Non-Games TF-Agents (12.5)

Flask and Deep Learning Keras/TensorFlow Web Services (13.1)

Resuming Training and Checkpoints in Python TensorFlow Keras (13.2)

Using a Keras Deep Neural Network with a Web Application (13.3)

When to Retrain Your Neural Network (13.4)

Keras and Google Tensor Processing Units (TPUs) (13.5)

AutoML with Auto-Keras (14.1)

Using Denoising AutoEncoders in Keras (14.2)

Anomaly Detection in Keras with AutoEncoders (14.3)

Training an Intrusion Detection System with Keras and KDD99 (14.4)

New Deep Learning Technology for Course (14.5)

How to Install TensorFlow GPU for Mac M1/M2 with Conda