TensorFlow Innovation Hub - Build Cutting-Edge Machine Learning Models
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Skill level
All levels
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Sections
10
03
Lectures
69
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Instructor
John Bura
What's inside
This course includes.
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10
Sections
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69
Lectures
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65
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.
+ 01 Intro to Tensorflow 2 10 lectures
00 Course Intro
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01 Intro to Tensorflow
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02 Installing Tensorflow
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03 Intro to Linear Regression
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04 Linear Regression Model - Creating Dataset
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05 Linear Regression Model - Building the Model
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06 Linear Regression Model - Creating a Loss Function
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07 Linear Regression Model - Training the Model
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08 Linear Regression Model - Testing the Model
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09 Summary and Outro
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+ 02 Image Recognition with MNIST 10 lectures
00 Course Intro
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01 Intro To Image Recognition
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02 Intro To MNIST
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03 Building A CNN Part 1 - Obtaining Data
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04 Building A CNN Part 2 - Building The Model
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05 Building A CNN Part 3 - Adding Loss And Optimizer Functions
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06 Building A CNN Part 4 - Train And Test Functions
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07 Building A CNN Part 5 - Train And Test The Mode
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08 MNIST Image Recognition With Keras Sequential Model
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09 Summary And Outro
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+ 02A Machine Learning: Beginners - Build Beginner Models in TensorFlow 2.0 2 lectures
00 Course Overview
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01 Build Models On The Web
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+ 03 Machine Learning: Beginners - AI Uninformed Search Algorithms 10 lectures
00 What Are Search Algorithms
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01 Depth First Search
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02 Build A Depth First Search Algorithm
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03 What Is Breadth First Search (BFS)
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04 Build A Breadth First Search Algorithm
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05 Depth Limited Search
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06 Iterative Deepening Depth First Search
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07 What Is Uniform Cost Search
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08 Build A Uniform Cost Search Algorithm
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09 Bidirectional Search
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+ 04 Machine Learning: Beginners - AI Informed Search Algorithms 4 lectures
00 What Are Informed Search Algorithms
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01 What Is Greedy Best-first Search
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02 Build A Greedy Best First Search Algorithm
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03 What Is A Search
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+ 05 Machine Learning: Beginners - How Machine Learning Works 9 lectures
00 How Does A Machine Learning Agent Learn
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01 What Is Inductive Learning
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02 Make Decisions With Decision Trees
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03 Performance Of A Machine Learning Algorithm
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04 Handle Noise In Data
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05 Statistical Learning
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08 Train The Model
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09 Test The Model
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10 Visualize Results
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+ 06 Machine Learning: Beginners - Logistic Regression 11 lectures
00 What Is Logistic Regression
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01 How To Prepare Data
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02 Prepare Data For Logistic Regression
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03 Build A Logistic Regression Model
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04 How To Build A Logistic Regression Model
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05 What Is Optimization
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06 How To Optimize A Logistic Regression Model
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07 Optimize The Logistic Regression Model
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08 Train The Model
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09 Test The Model
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10 Visualize Results
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+ 07 Machine Learning: Beginners - Gradient Boosted Classification 7 lectures
00 What Is Gradient Boosting
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01 Prepare Data For Gradient Boosted Classification
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02 Build Binary Classes
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03 How To Shape Data For Classification
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04 Shape Data For Classification
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05 How To Build A Boosted Trees Classifier
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06 Build A Boosted Trees Classifier
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+ 08 Machine Learning: Beginners - Gradient Boosted Regression 3 lectures
00 Build Input Functions
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01 Build A Boosted Trees Regressor
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02 Train And Evaluate The Model
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+ 09 Machine Learning Intermediate - Supervised Learning Introduction 3 lectures
00 What You'll Learn
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01 What Is Supervised Learning
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02 Build Models On The Web
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Instructors
Taught by people who ship.
John Bura
Founder and CEO of Mammoth Club and Course Pro, the #1 AI-powered Learning Management System for course and content development, training and evaluation.
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