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 MatDescriptionlib

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 MatDescriptionlib

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

Screenshots

Citación :

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