TensorFlow is an end-to-end open source platform for machine learning. This four day course explores all aspects of machine learning and teaches the participant how to build deep learning applications with Tensor. The class is a hands-on experience building state-of-the-art image classifiers and other deep learning models.

4 days - $2,100.00

Course taught by an expert Artificial Intelligence coder.

Prerequisites:

Basic understatnding of artificial intelligence and machine learning are required.  Knowledge of Python and Algebra are also essential. 

Course Outline 

Machine Learning and Deep Learning Overview
Mathematical Concepts
ML Overview
DL Overview
TensorFlow: Overview and Basics

TensorFlow: What is it? History and Background
Use cases and Key Applications
Machine Learning and Deep Learning Basics
Environment, Configuration Settings and Installation
TensorFlow Primitives
Declaring Tensors
Declaring Placeholders and Variables
Working with Matrices
Declaring Operations
Operations in Computational Graph
Nested Operations
Multiple Layers
Implementing Loss Functions
Implementing Back Propagation
Machine Learning With TensorFlow

Linear Regression Review
Linear Regression Using TensorFlow
Support Vector Machines (SVM) Review
SVM using TensorFlow
Nearest Neighbor Method Review
Nearest Neighbor Method using TensorFlow
Neural Networks With TensorFlow

Neural Networks Review
Optimization and Operational Gates
Working with Activation Functions
Implementing One-Layer Neural Network
Implementing Different Layers
Implementing Multilayer Neural Networks
Deep Neural Networks With TensorFlow

Models and Overview
Convolutional Neural Network Overview and Implementation
CNN Architecture
Recurrent Neural Network Overview and Implementation
RNN Architecture
Additional Topics

TensorFlow Extensions
Scikit Flow
TFLearn
TF-Slim
TensorLayer
Keras
Unit Testing
Taking your implementation to production