[Udemy] TensorFlow and the Google Cloud ML Engine for Deep Learning

[Udemy] TensorFlow and the Google Cloud ML Engine for Deep Learning
Table of Contents
1

Introduction

2

Installation

3

TensorFlow and Machine Learning

4

Working with Images

5

K-Nearest-Neighbors with TensorFlow

6

Linear Regression with a Single Neuron

7

Linear Regression in TensorFlow

8

Logistic Regression in TensorFlow

9

The Estimator API

10

Neural Networks and Deep Learning

11

Classifiers and Classification

12

Convolutional Neural Networks (CNNs)

13

Recurrent Neural Networks (RNNs)

14

Unsupervised Learning

15

TensorFlow on the Google Cloud

16

TensorFlow Using Cloud ML Engine

17

Feature Engineering and Hyperparameter Tuning

About this course

CNN's, RNNs and other neural networks for unsupervised and supervised deep learning

Requirements

  • Basic proficiency at programming in Python
  • Basic understanding of machine learning models is useful but not required

Description

TensorFlow is quickly becoming the technology of choice for deep learning, because of how easy TF makes it to build powerful and sophisticated neural networks. The Google Cloud Platform is a great place to run TF models at scale, and perform distributed training and prediction.

This is a comprehensive, from-the-basics course on TensorFlow and building neural networks. It assumes no prior knowledge of Tensorflow, all you need to know is basic Python programming.

What's covered:

  • Deep learning basics: What a neuron is; how neural networks connect neurons to 'learn' complex functions; how TF makes it easy to build neural network models
  • Using Deep Learning for the famous ML problems: regression, classification, clustering and autoencoding
  • CNNs - Convolutional Neural Networks: Kernel functions, feature maps, CNNs v DNNs 
  • RNNs - Recurrent Neural Networks: LSTMs, Back-propagation through time and dealing with vanishing/exploding gradients
  • Unsupervised learning techniques - Autoencoding, K-means clustering, PCA as autoencoding 
  • Working with images
  • Working with documents and word embeddings
  • Google Cloud ML Engine: Distributed training and prediction of TF models on the cloud
  • Working with TensorFlow estimators

 

Who this course is for:

  • Developers who want to understand and build ML and deep learning models in TensorFlow
    • Data scientists who want to learn cutting edge TensorFlow technology

CrunchLearn is a platform to Watch Courses and tutorials for Free. Learn Machine Learning, Cloud computing, Big Data, DevOps, Hacking, Photoshop, Coding, Programming, IT & Software, Marketing, Music and more.

Terms Privacy policy

Copyright 2021 © All rights reserved.