Valkov V. Hacker's Guide to Machine Learning with Python

Leanpub, 2019. — 259 p.Deep Learning has revolutionized the Machine Learning field. Python tools like Scikit-Learn, Pandas, TensorFlow, and Keras allows you to develop applications powered by Machine Learning. This book is written for you, the Machine Learning practitioner. Every chapter describes a problem and a solution that you'll encounter in your Machine Learning Journey.Get started with TensorFlow 2 and Keras.
Deploy a complete Keras Deep Learning project to production with Flask.
Use the Keras library to train Deep Neural Networks.
Learn how to handle imbalanced datasets.
Hyperparameter tuning with Keras Tuner.
Learn how to debug your model when it is underfitting or overfitting.
Predict cryptocurrency prices using LSTMs.TensorFlow 2 and Keras - Quick Start Guide.
End to End Machine Learning Project.
Build Your First Neural Network.
Heart Disease Prediction.
Cryptocurrency price prediction using LSTMs.
Handling Imbalanced Datasets.
Fixing Underfitting and Overfitting Models.
Hyperparameter Tuning.
Data Preprocessing.
Fundamental Machine Learning Algorithms.
Time Series Forecasting.
Demand Prediction for Multivariate Time Series with LSTMs.
Time Series Classification for Human Activity Recognition with LSTMs in Keras.
Time Series Anomaly Detection with LSTM Autoencoders using Keras in Python.
Object Detection.
Image Data Augmentation.
Sentiment Analysis with TensorFlow 2 and Keras using Python.True PDF