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The abundance of data and affordable cloud scale has led to an explosion of interest in Deep Learning. Google has released an excellent library called TensorFlow to open-source, allowing state-of-the-art machine learning done at scale, complete with GPU-based acceleration.

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Last Updated

March 4, 2021

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This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course.In this course you learn about:

· Core Deep Learning and Machine Learning math essentials

· TensorFlow Overview and Basics.

· TensorFlow Operations

· Neural Networks With TensorFlow

· Deep Learning With TensorFlow

Course Curriculum

    • This is summary of ML/DL Concepts (from the class – Machine Learning & Deep Learning Fundamentals) 00:00:00
    • TensorFlow – What is it? History & Background 00:00:00
    • Use cases & Key Applications 00:00:00
    • Machine Learning & Deep Learning Basics 00:00:00
    • Environment, Configuration Settings & Installation 00:00:00
    • TensorFlow Primitives 00:00:00
    • Declaring Tensors 00:00:00
    • Declaring Placeholders and Variables 00:00:00
    • Working with Matrices 00:00:00
    • Declaring Operations 00:00:00
    • Operations in Computational Graph 00:00:00
    • Nested Operations 00:00:00
    • Multiple Layers 00:00:00
    • Implementing Loss Functions 00:00:00
    • Implementing Back Propagation 00:00:00
    • Linear Regression Review 00:00:00
    • Linear Regression Using TensorFlow 00:00:00
    • Support Vector Machines (SVM) Review 00:00:00
    • SVM using TensorFlow 00:00:00
    • Nearest Neighbor Method Review 00:00:00
    • Nearest Neighbor Method using TensorFlow 00:00:00
    • Neural Networks Review 00:00:00
    • Optimization and Operational Gates 00:00:00
    • Working with Activation Functions 00:00:00
    • Implementing One-Layer Neural Network 00:00:00
    • Implementing Different Layers 00:00:00
    • Implementing Multilayer Neural Networks 00:00:00
    • Models and Overview 00:00:00
    • Single Hidden Layer 00:00:00
    • Multiple Hidden Layer 00:00:00
    • Convolutional Neural Network Overview & Implementation 00:00:00
    • CNN Architecture 00:00:00
    • Recurrent Neural Network Overview & Implementation 00:00:00
    • RNN Architecture 00:00:00
    • TensorFlow Extensions 00:00:00
    • Unit Testing 00:00:00
    • Taking your implementation to production 00:00:00
    • Other Misc Topics 00:00:00

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