Tensorflow 2 & Keras:Deep Learning & Artificial Intelligence

欢迎使用Tensorflow 2和Keras API课程学习深度学习和人工智能。

本课程包括如何使用tensorflow 2以及如何使用tensorflow 2和Keras创建深度学习应用程序。

本课程将指导您如何使用google colab，以及动手完成google colab的所有工作。

此课程中包含的许多项目，例如MNIST数字分类，MNIST时尚数据分类，猫和狗图像分类，面部表情识别，叶病识别，使用Keras生成带有DCGANs（深度卷积生成对抗网络）的图像，使用Keras生成的自动降噪编码器，TensorFlow以及深度学习等。

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | VTT | Size: 2.69 GB | Duration: 8h 28m

What you’ll learn
Complete Understanding of TensorFlow 2 (Google’s Deep Learning Framework) from the Scratch
Keras API to quickly build models that run on Tensorflow 2
Learn How Neural Network works
Understand Backpropagation, Forward Propogation, Gradient Descent
Artificial Neural Networks (ANNs)
Convolutional Neural Networks (CNNs)
Perform Image Classification with Convolutional Neural Networks
Image Recognition
Recurrent Neural Networks (RNNs)
Transfer Learning
Create Generative Adversarial Networks (GANs) with TensorFlow
Autoencoders
Generative Deep Learning – Neural Style Transfer
Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib

Description
Welcome to Deep Learning and Artificial Intelligence with Tensorflow 2 and Keras API Course.

This course includes how to work with tensorflow 2 and creates Deep Learning applications with tensorflow 2 and Keras.

This course guide you how to work with google colab, all the hands on work done in google colab.

Many Projects included in this course like MNIST Digits Classification, MNIST Fashion data classification, Cat and Dog images Classification, Facial Expression Recognition, Leaf disease recognition, Generate Images with DCGANs(Deep Convolutional Generative Adversarial Networks) with Keras, Denoising autoencoders with Keras, TensorFlow, and Deep Learning etc.

Generative Deep Learning – Neural Style Transfer also included in this course.

For every lecture reference notes and code file is attached in this course.

Tensorflow is an open source machine library, and is one of the most widely used frameworks for deep learning.

Google released a new version of their TensorFlow deep learning library (TensorFlow 2) that integrated the Keras API directly and promoted this interface as the default or standard interface for deep learning development on the platform.

This course includes various topics –

Complete Understanding of TensorFlow 2.0 (Google’s Deep Learning Framework)

from the Scratch

Keras API to quickly build models that run on Tensorflow 2

Learn How Neural Network works

Understand Backpropagation, Forward Propogation, Gradient Descent

Artificial Neural Networks (ANNs)

Convolutional Neural Networks (CNNs)

Perform Image Classification with Convolutional Neural Networks

Image Recognition

Recurrent Neural Networks (RNNs)

Transfer Learning

Create Generative Adversarial Networks (GANs) with TensorFlow

Autoencoders

Introduction to Natural Language Processing

Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib

Who this course is for:
Anyone Passionate about Deep Learning and Artificial Intelligence
Python Developer curious about Deep Learning and Tensorflow