Build Machine Learning Websites with Tensorflow.js
Created by Team Mammoth
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Skill level
All levels
02
Sections
18
03
Lectures
103
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Instructor
Team Mammoth
What's inside
This course includes.
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18
Sections
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103
Lectures
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103
Resources
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Certificate of completion
Included
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Mobile and desktop access
Included
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AI learning assistance
Included
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Course content
Curriculum & lectures.
+ 00a Course Overview 5 lectures
00-01 What You'll Learn
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00-02 What Is Tensorflow Js
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00-03 Load Tensorflow Object
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01 What Is Machine Learning
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Full Course Source Files
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+ Introduction to the Course 6 lectures
01 01 Introduction To The Course
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01 02 Introduction Of The Instructor
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01 03 Why Should You Learn Javascript
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01 04 Quick Win
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01 05 Course Requirements
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+ Variable and Data Types 9 lectures
02 01 What Will We Learn In This Section
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02 02 Variables
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02 03 Data Types
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02 04 Variable Mutation
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02 05 Type Coercion
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02 06 Coding Challenge
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02 07 Coding Challenge Solution
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02 08 Section Summary
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+ Operators 7 lectures
03 01 What Will We Learn In This Section
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03 02 Basic Operators
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03 03 Operator Precedence
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03 04 Coding Challenge
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03 05 Coding Challenge Solution
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03 06 Section Summary
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+ Conditional Statements 10 lectures
04 01 What Will We Learn In This Section
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04 02 If Else Statements
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04 03 Boolean Logic
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04 04 Switch Statements
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04 05 Truthy And Falsie Values
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04 06 Equality Operators
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04 07 Coding Challenge
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04 08 Coding Challenge Solution
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04 09 Section Summary
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+ Functions and Arrays 7 lectures
05 01 What Will We Learn In This Section
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05 02 Functions
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05 03 Function Statements And Expressions
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05 04 Arrays
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05 05 Coding Challenge
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05 06 Section Summary
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+ Objects 8 lectures
06 01 What Will We Learn In This Section
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06 02 Objects And Properties
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06 03 Objects And Methods
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06 04 Objects Vs Primitives
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06 05 Coding Challenge
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06 06 Coding Challenge Solution
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06 07 Section Summary
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+ Loops 7 lectures
07 01 What Will We Learn In This Section
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07 02 Loops
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07 03 Iteration
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07 04 Coding Challenge
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07 05 Coding Challenge Solution
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07 06 Section Summary
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+ JavaScript Execution 12 lectures
08 01 What Will We Learn In This Section
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08 02 Javasript Parsers And Engines
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08 03 Execution Contexts And Execution Stack
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08 04 Creation And Execution Phases
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08 05 Hoisting
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08 06 Scoping
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08 07 Scope Chain
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08 08 This Keyword
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08 09 Coding Challenge
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08 10 Coding Challenge Solution
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08 11 Section Summary
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Source Files (6)
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+ 01a Build Your First Tensors 5 lectures
00 Linear Algebra For Machine Learning
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01 Build Tensors
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02 Tensor Utility Methods
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03 Perform Math With Tensors
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+ 01b Visualize Data 3 lectures
01b-01 Build A Scatter Plot
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01b-02 Build A Bar Chart
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01b-03 Build A Histogram
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+ 01c Train a Simple Model 3 lectures
01c-01 Build Sample Data
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01c-02 Build The Model
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01c-03 Make A Prediction
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+ 01d Generate and Visualize Data 2 lectures
01d-01 Generate Data
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01d-02 Visualize Data
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+ 02 Build a Linear Regression Model 4 lectures
02-00 What Is Linear Regression
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02-01 Prepare Training Data
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02-02 Build The Model
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02-03 Make A Prediction
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+ 02b Visualize Linear Regression with User Input 5 lectures
02b-01 Set Up The Canvas
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02b-02 Draw A Data Sample
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02b-03 Create Loss And Prediction Functions
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02b-04 Collect User Input For Data
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02b-05 Visualize Linear Regression With Dynamic Data
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+ 03 Visualize Polynomial Regression with User Input 2 lectures
03-01 Set Up The Canvas
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03-02 Visualize Linear Regression With Dynamic Data
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+ 04 Polynomial Regression 5 lectures
04-01 Generate Samples
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04-02 Generate A Prediction Equation With Weights
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04-03 Train The Model
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04-04 Visualize Predictions
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04-05 Visualize Prediction Error
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+ 05 K Nearest Neighbors Image Classification with Tensorflow JS 3 lectures
05-01 Load Models Into Html
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05-02 Train Model On Images
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05-03 Make A Prediction
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Instructors
Taught by people who ship.
Team Mammoth
Instructor
Produced by a team of Mammoth Club industry experts. Over 14 years, Mammoth Club has built a global student community in 190+ countries with 9+ million courses sold, releasing over 1,000+ courses and 5,000+ hours of video content.
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