Deep Learning with Python

Hello Everyone, I'm Shubham, a PhD student; in this repository, I'm implementing the book "Deep Learning with Python - Jason Brownlee".

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The Syllabus:

1. The Introduction and Basic Part

   1. Deep Learning Introduction
   2. Introduction to Theano
   3. Introduction to TensorFlow
   4. Introduction to Keras
   5. Project: Develop Large Models on GPUs Cheaply In the Cloud

2. Multilayer Perceptrons

   1. Multilayer Perceptrons
   2. First Neural Network With Keras
   3. The Performance of Deep Learning Models
   4. Keras Models With Scikit-Learn For General Machine Learning
   5. Multiclass Classification Of Flower Species
   6. Binary Classification Of Sonar Returns
   7. Regression Of Boston House Prices

3. Advanced Multilayer Perceptrons and Keras

   1. Save Your Models For Later With Serialization
   2. Keep The Best Models During Training With Checkpointing
   3. Understand Model Behavior During Training By Plotting History
   4. Reduce Overfitting With Dropout Regularization
   5. Lift Performance With Learning Rate Schedules

4. Convolutional Neural Networks

   1. Introduction to Convolutional Neural Networks
   2. Handwritten Digit Recognition
   3. Improve Model Performance With Image Augmentation
   4. Object Recognition in Photographs
   5. Predict Sentiment From Movie Reviews

5. Recurrent Neural Networks

   1. Recurrent Neural NetworksTime Series Prediction with LSTM Recurrent Neural Networks
   2. Time Series Prediction with Multilayer Perceptrons
   3. Time Series Prediction with LSTM Recurrent Neural Networks
   4. Sequence Classification of Movie Reviews
   5. Understanding Stateful LSTM Recurrent Neural Networks
   6. Text Generation With Alice in Wonderland

6. Future Work