Here we will learn :
TensorFlow – Basics
TensorFlow – TensorBoard Visualization
TensorFlow – Introduction
TensorFlow – Installation
Understanding Artificial Intelligence
TensorFlow – Mathematical Foundations
Machine Learning and Deep Learning
TensorFlow – Convolutional Neural Networks
TensorFlow – Recurrent Neural Networks
TensorFlow – Word Embedding
TensorFlow – Single Layer Perceptron
TensorFlow – Linear Regression
TensorFlow – TFLearn And Its Installation
TensorFlow – CNN And RNN Difference
TensorFlow – Keras
TensorFlow – Distributed Computing
TensorFlow – Exporting
TensorFlow – Multi-Layer Perceptron Learning
TensorFlow – Hidden Layers of Perceptron
TensorFlow – Optimizers
TensorFlow – XOR Implementation
TensorFlow – Gradient Descent Optimization
TensorFlow – Forming Graphs
Image Recognition using TensorFlow
Recommendations for Neural Network Training
TensorFlow – Quick Guide
Curriculum
- 26 Sections
- 87 Lessons
- 10 Weeks
- TensorFlow - BasicsIn this chapter, we will learn about the basics of TensorFlow. We will begin by understanding the data structure of tensor.4
- TensorFlow - TensorBoard Visualization2
- TensorFlow - Introduction2
- TensorFlow - Installation6
- Understanding Artificial Intelligence3
- TensorFlow - Mathematical Foundations3
- Machine Learning and Deep Learning6
- TensorFlow - Convolutional Neural Networks3
- TensorFlow - Recurrent Neural Networks2
- TensorFlow - Word Embedding2
- TensorFlow - Single Layer Perceptron3
- TensorFlow - Linear Regression2
- TensorFlow - TFLearn And Its Installation2
- TensorFlow - CNN And RNN Difference2
- TensorFlow - Keras2
- TensorFlow - Distributed Computing1
- TensorFlow - Exporting1
- TensorFlow - Multi-Layer Perceptron Learning1
- TensorFlow - Hidden Layers of Perceptron1
- TensorFlow - Optimizers2
- TensorFlow - XOR Implementation2
- TensorFlow - Gradient Descent Optimization3
- TensorFlow - Forming Graphs1
- Image Recognition using TensorFlow1
- Recommendations for Neural Network Training7
- TensorFlow - Quick Guide23
- 26.1TensorFlow – Introduction
- 26.2TensorFlow – Installation
- 26.3Understanding Artificial Intelligence
- 26.4Machine Learning and Deep Learning
- 26.5TensorFlow – Basics
- 26.6TensorFlow – Convolutional Neural Networks
- 26.7TensorFlow – Recurrent Neural Networks
- 26.8TensorFlow – TensorBoard Visualization
- 26.9TensorFlow – Word Embedding
- 26.10TensorFlow – Single Layer Perceptron
- 26.11TensorFlow – Linear Regression
- 26.12TensorFlow – TFLearn And Its Installation
- 26.13TensorFlow – CNN And RNN Difference
- 26.14TensorFlow – Distributed Computing
- 26.15TensorFlow – Exporting
- 26.16TensorFlow – Multi-Layer Perceptron Learning
- 26.17TensorFlow – Hidden Layers of Perceptron
- 26.18TensorFlow – Optimizers
- 26.19TensorFlow – XOR Implementation
- 26.20TensorFlow – Gradient Descent Optimization
- 26.21TensorFlow – Forming Graphs
- 26.22Image Recognition using TensorFlow
- 26.23Recommendations for Neural Network Training
