Deep Learning With TensorFlow

 Overview:

Robusta’s Deep Learning with TensorFlow course has been crafted by industry experts and aligned with the latest best practices to transform you into deep learn ing expert. You’ll learn to master deep learning concepts and the TensorFlow open source framework, implement deep learning algorithms, build artificial neural networks, and traverse layers of data abstraction to understand the power of data and prepare you for an exciting career in deep learning.

Duration: 

40 hours

Intended Audience:

There is booming demand for skilled deep learning engineers across a wide range of industries, making this deep learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this deep learning online course particularly for the following professionals:

-          Software engineers

-          Data scientists

-          Data analysts

-          Statisticians with an interest in deep learning

Prerequisites:

Participants in this Deep Learning course should have:

-          Familiarity with programming fundamentals

-          Fair understanding of basics of statistics and mathematics

Cousre Objectives:

By the end of this deep learning course with TensorFlow, you will be able to accomplish the following:

-          Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline

-          Implement deep learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before

-          Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces

-          Build deep learning models in TensorFlow and interpret the results

-          Understand the language and fundamental concepts of artificial neural networks

-          Troubleshoot and improve deep learning models

-          Build your own deep learning project

-          Differentiate between machine learning, deep learning and artificial intelligence

 Course outlines:

1.      Deep Learning with TensorFlow

• Introduction to TensorFlow
• Perceptrons
• Activation Functions
• Artificial Neural Networks
• Gradient Descent and Backpropagation
• Optimization and Regularization
• Intro to Convolutional Neural Networks
• Introduction to Recurrent Neural Networks
• Deep Learning applications

2.      Math Refresher

3.      Deep Learning Fundamentals

• Learning Objectives
• Introduction to Deep Learning
• Deep Learning Models
• Additional Deep Learning Models
• Deep Learning Platforms & Libraries