Books & Videos

Table of Contents

Chapter: Exploring and Transforming Data

The Course Overview

03m 24s

TensorFlow's Main Data Structure and Tensors

07m 14s

Handling the Computing Workflow and TensorFlow's Data Flow Graph

05m 25s

Basic Tensor Methods

08m 22s

How TensorBoard Works?

05m 32s

Reading Information from Disk

04m 0s

Chapter: Clustering

Learning from Data and Unsupervised Learning

02m 15s

Mechanics of k-Means

03m 34s

k-Nearest Neighbor

05m 33s

Project 1 and k-Means Clustering on Synthetic Datasets

04m 7s

Project 2 and Nearest Neighbor on Synthetic Datasets

01m 52s

Chapter: Linear Regression

Univariate Linear Modelling Function

04m 53s

Optimizer Methods in TensorFlow and The Train Module

03m 11s

Univariate Linear Regression

05m 10s

Multivariate Linear Regression

05m 14s

Chapter: Logistic Regression

Logistic Function Predecessor and The Logit Functions

04m 7s

The Logistic Function

05m 53s

Univariate Logistic Regression

06m 55s

Univariate Logistic Regression with skflow

02m 27s

Chapter: Simple FeedForward Neural Networks

Preliminary Concepts

07m 41s

First Project and Non-Linear Synthetic Function Regression

02m 31s

Second Project and Modeling Cars Fuel Efficiency with Non-Linear Regression

03m 5s

Third Project and Learning to Classify Wines: Multiclass Classification

02m 56s

Chapter: Convolutional Neural Networks

Origin of Convolutional Neural Networks

03m 26s

Applying Convolution in TensorFlow

03m 55s

Subsampling Operation and Pooling

02m 56s

Improving Efficiency and Dropout Operation

02m 15s

Convolutional Type Layer Building Methods

01m 2s

MNIST Digit Classification

03m 30s

Image Classification with the CIFAR10 Dataset

02m 27s

Chapter: Recurrent Neural Networks and LSTM

Recurrent Neural Networks

03m 39s

A Fundamental Component and Gate Operation and Its Steps

04m 23s

TensorFlow LSTM Useful Classes and Methods

02m 1s

Univariate Time Series Prediction with Energy Consumption Data

02m 36s

Writing Music "a la" Bach

08m 6s

Chapter: Deep Neural Networks

Deep Neural Network Definition and Architectures Through Time

02m 34s


03m 52s

Inception V3

00m 59s

Residual Networks (ResNet)

02m 6s

Painting with Style and VGG Style Transfer

03m 10s

Chapter: Library Installation and Additional Tips

Windows Installation

02m 38s

Mac OS X Installation

02m 57s