[Packtpub] Master-Deep-Learning-with-TensorFlow-2.0-in-Python-2019

By Course Club Last updated Sep 22, 2019

July 19, 2019

4 hours 55 minutes

Build deep learning algorithms with TensorFlow 2.0, dive into neural networks, and apply your skills in a business case.

More Information

Learn

Gain a strong understanding of TensorFlow – Google’s cutting-edge deep learning framework
Understand backpropagation, Stochastic Gradient Descent, batching, momentum, and learning rate schedules
Master the ins and outs of underfitting, overfitting, training, validation, testing, early stopping, and initialization
Competently carry out pre-processing, standardization, normalization, and one-hot encoding

About

Data scientists, machine learning engineers, and AI researchers all have their own skillsets. But what special quality do they have in common?

They are all masters of deep learning.

We often hear about AI, or self-driving cars, or algorithmic magic at Google, Facebook, and Amazon. But it is not magic – it is deep learning. And more specifically, it is usually deep neural networks – the single algorithm that rules them all.

In this course, we’ll teach you to master Deep Learning. We start with the basics and take you step by step toward building your very first (or second, or third…) deep learning algorithm; we program everything in Python and explain each line of code. We do this early on to give you the confidence to progress to the more complex topics we cover

All sophisticated concepts we teach are explained intuitively. You’ll get fully acquainted with TensorFlow and NumPy, two tools that are essential for creating and understanding Deep Learning algorithms. You’ll explore layers, their building blocks, and activations – sigmoid, tanh, ReLu, softmax, and more. You’ll understand the backpropagation process, intuitively and mathematically. You’ll be able to spot and prevent overfitting, one of the biggest issues in machine and deep learning. You’ll master state-of-the-art initialization methods. Don’t know what initialization is? We explain that, too. you’ll learn how to build deep neural networks using real data, implemented by real companies in the real world—templates included! Also, you will create your very own deep learning algorithm. Take the first step toward a satisfying data science career and becoming a Master of Deep Learning. All the code files are placed at https://github.com/PacktPublishing/Master-Deep-Learning-with-TensorFlow-2.0-in-Python-2019
Features	Build deep learning algorithms from scratch in Python using NumPy and TensorFlow Set yourself apart from the competition with hands-on deep- and machine-learning experience Grasp the math behind deep learning algorithms
Course Length	4 hours 55 minutes
ISBN	9781839218163
Date Of Publication	19 Jul 2019

Size: 2.29 GB

Download Now

https://github.com/PacktPublishing/Master-Deep-Learning-with-TensorFlow-2.0-in-Python-2019.