ratings
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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Certification
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
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- This is summary of ML/DL Concepts (from the class – Machine Learning & Deep Learning Fundamentals) 00:00:00
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- 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
- 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
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