TensorFlow 2.0 Masterclass: Hands-On Deep Learning and AI-0daytown

h264, yuv420p, 1280×720 |ENGLISH, aac, 44100 Hz, 2 channels, s16 | 13h 55mn | 6.2 GB
Instructor: Vijay Gadhave

Work on 6 Projects, Learn Deep Learning, AI, Keras, Python, ANN, CNN, RNN, LSTM, Transfer Learning, Autoencoder, NLP !

What you’ll learn

Complete Understanding of TensorFlow 2.0 from the Scratch
Artificial Neural Networks (ANNs)
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Transfer Learning
Autoencoders
Natural Language Processing
Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib

Requirements

Python Programming Basics
Machine Learning Basics

Description

Google has recently released TensorFlow 2.0, it has so many features that simplify the Model Development, Maintenance, Processes and Performance…

Why TensorFlow 2.0 ?

Whether you’re an expert or a beginner, TensorFlow 2.0 is an end-to-end platform that makes it easy for you to build and deploy ML models

With the TensorFlow 2.0,

1) Building the Model is very Easy

2) Robust ML production anywhere

3) Powerful experimentation for research

With this course you will have the Complete Understanding of TensorFlow 2.0 from very Beginning !

List of the Projects,

Project 1: CNN for Digit Recognition

Project 2: CNN for Breast Cancer Detection

Project 3: CNN for Predicting the Bank Customer Satisfaction

Project 4: CNN for Credit Card Fraud Detection

Project 5: RNN – LSTM for IMDB Review Classification

Project 6: Google Stock Price Prediction with RNN and LSTM

Main Topics Covered in this Course,

Part 1: Introduction (Section 1)

Part 2: Artificial Neural Networks (Section 2 – Section 4)

Part 3: Convolutional Neural Networks (Section 5 – Section 11)

Part 4: Recurrent Neural Networks (Section 12 – Section 15)

Part 5: Transfer Learning

Part 6: Autoencoders

Part 7: Natural Language Processing (Section 16)

Part 8: Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib (Section 17 – Section 19)

Regards,

Vijay Gadhave
Who this course is for:

Anyone who wants to start a career in the field of Data Science
Anyone Passionate about Deep Learning and Artificial Intelligence

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