Programming With Python: 4 Manuscripts - Deep Learning With Keras, Convolutional Neural Networks In Python, Python Machine Learning, Machine Le

By Frank Millstein

Programming With Python - 4 BOOK BUNDLE Deep Learning with KerasHere Is a Preview of What You'll Learn Here...The difference between deep learning and machine learningDeep neural networksConvolutional neural networksBuilding deep learning models with KerasMulti-layer perceptron network modelsActivation functionsHandwritten recognition using MNISTSolving multi-class classification problemsRecurrent neural networks and sequence classificationAnd much more...Convolutional Neural Networks in PythonHere Is a Preview of What You'll Learn In This Book... Convolutional neural networks structure How convolutional neural networks actually work Convolutional neural networks applications The importance of convolution operator Different convolutional neural networks layers and their importance Arrangement of spatial parameters How and when to use stride and zero-padding Method of parameter sharing Matrix multiplication and its importance Pooling and dense layers Introducing non-linearity relu activation function How to train your convolutional neural network models using backpropagation How and why to apply dropout CNN model training process How to build a convolutional neural network Generating predictions and calculating loss functions How to train and evaluate your MNIST classifier How to build a simple image classification CNN And much, much more Python Machine LearningHere Is A Preview Of What You'll Learn Here...Basics behind machine learning techniques Different machine learning algorithms Fundamental machine learning applications and their importanceGetting started with machine learning in Python, installing and starting SciPy Loading data and importing different libraries Data summarization and data visualization Evaluation of machine learning models and making predictions Most commonly used machine learning algorithms, linear and logistic regression, decision trees support vector machines, k-nearest neighbors, random forests Solving multi-clasisfication problems Data visualization with Matplotlib and data transformation with Pandas and Scikit-learn Solving multi-label classification problems And much, much more... Machine Learning With TensorFlowHere Is a Preview of What You'll Learn Here...What is machine learningMain uses and benefits of machine learningHow to get started with TensorFlow, installing and loading data Data flow graphs and basic TensorFlow expressions How to define your data flow graphs and how to use TensorBoard for data visualization Main TensorFlow operations and building tensorsHow to perform data transformation using different techniquesHow to build high performance data pipelines using TensorFlow Dataset frameworkHow to create TensorFlow iterators Creating MNIST classifiers with one-hot transformationGet this book bundle NOW and SAVE money

• Format: Paperback
• Language: English
• ISBN: 1719443718
• ISBN13: 9781719443715
• Release Date: May 2018
• Publisher: Createspace Independent Publishing Platform
• Length: 498 Pages
• Weight: 1.08 lbs.
• Dimensions: 1.0" x 5.0" x 8.0"