Understanding the Foundations of TensorFlow

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Janani Ravi

2:44:27

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01 - Course Overview

01 - Course Overview.mp4

01:57

02 - Introducing TensorFlow

02 - Prerequisites and Course Overview.mp4

03:28

03 - Traditional ML Algorithms.mp4

08:23

04 - Representation ML Algorithms.mp4

02:18

05 - Deep Learning and Neural Networks.mp4

04:14

06 - Introducing TensorFlow.mp4

04:18

07 - The World as a Graph.mp4

02:57

08 - Downloading and Installing TensorFlow.mp4

08:17

03 - Introducing Computation Graphs

09 - The Computation Graph.mp4

03:52

10 - Modeling Cyclic Dependencies.mp4

02:55

11 - Building, Running, and Visualizing Graphs.mp4

07:53

12 - Computation Graphs and Distributed Systems.mp4

01:54

13 - Simple Math Operations.mp4

05:50

14 - Tensors.mp4

04:28

15 - Rank of a Tensor.mp4

01:11

16 - Tensor Math.mp4

03:41

17 - Numpy and TensorFlow.mp4

02:48

04 - Digging Deeper into Fundamentals

18 - A TensorFlow Example - Linear Regression.mp4

06:33

19 - Linear Regression in Practice.mp4

02:54

20 - Placeholders.mp4

05:26

21 - Fetches and the Feed Dictionary.mp4

05:22

22 - Variables.mp4

08:01

23 - Default and Explicitly Specified Graphs.mp4

03:20

24 - Named Scopes.mp4

04:09

25 - Interactive Sessions.mp4

01:50

26 - Quick Overview - Linear Regression in TensorFlow.mp4

04:16

05 - Working with Images

27 - Image Recognition and Neural Networks.mp4

03:12

28 - Representing Images as Tensors.mp4

03:53

29 - Transposing Images.mp4

05:29

30 - Resizing Images.mp4

06:51

31 - Representing a List of Images as a 4D Tensor.mp4

06:35

06 - Solving Basic Math Functions

32 - The MNIST Dataset.mp4

03:20

33 - The K-nearest-neighbors Algorithm.mp4

06:41

34 - L1 Distance.mp4

02:47

35 - KNN in TensorFlow.mp4

06:18

36 - Calculating L1 in TensorFlow.mp4

04:16

37 - Measuring Accuracy.mp4

02:50

Description

This course introduces TensorFlow, an open source data flow library for numerical computations using data flow graphs.

What You'll Learn?

In this course, Understanding the Foundations of TensorFlow, you'll learn the TensorFlow library from very first principles. First, you'll start with the basics of machine learning using linear regression as an example and focuses on understanding fundamental concepts in TensorFlow. Next, you'll discover how to apply them to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions, and the computation graph. Then, you'll be introduced to TensorBoard, the visualization tool used to view and debug the data flow graphs. You'll work with basic math operations and image transformations to see how common computations are performed. Finally, you'll solve a real world machine learning problem using the MNIST handwritten dataset and the k-nearest-neighbours algorithm. By the end of this course, you'll have a better understanding of the foundations of TensorFlow.

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Machine Learning

TensorFlow

Janani Ravi

Instructor's Courses

Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing high-quality content for technical skill development. Loonycorn is working on developing an engine (patent filed) to automate animations for presentations and educational content.

Pluralsight

View courses Pluralsight

Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.