Deep Learning for Beginners in Python: Work On 12+ Projects

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New |h264, yuv420p, 1280×720 |ENGLISH, 44100 Hz, 2 Channels | 14h 34mn | 6 GB

What you’ll learn

Complete Understanding of Deep Learning from the Scratch
Building the Artificial Neural Networks (ANNs) from the Scratch
Artificial Neural Networks (ANNs) for Binary Data Classification
Building Convolutional Neural Networks from the Scratch
Convolutional Neural Network for Image Classification
Convolutional Neural Network for Digit Recognition
Breast Cancer Detection with Convolutional Neural Networks
Convolutional Neural Networks for Predictive Analysis
Convolutional Neural Networks for Fraud Detection
Building the Recurrent Neural Networks (ANNs) from Scratch
LSTM and GRU
Review Classification with LSTM and GRU
LSTM and GRU for Image Classification
Prediction of Google Stock Price with RNN and LSTM
Transfer Learning
Natural Language Processing
Crash Course on Numpy (Data Analysis)
Crash Course on Pandas (Data Analysis)
Crash course on Matplotlib (Data Visualization)

Requirements

Python Programming Basics

Description

The Artificial Intelligence and Deep Learning are growing exponentially in today’s world. There are multiple application of AI and Deep Learning like Self Driving Cars, Chat-bots, Image Recognition, Virtual Assistance, ALEXA, so on…

With this course you will understand the complexities of Deep Learning in easy way, as well as you will have A Complete Understanding of Googles TensorFlow 2.0 Framework

TensorFlow 2.0 Framework has amazing features that simplify the Model Development, Maintenance, Processes and Performance

In TensorFlow 2.0 you can start the coding with Zero Installation, whether you’re an expert or a beginner, in this course you will learn an end-to-end implementation of Deep Learning Algorithms

List of the Projects that you will work on,

Deep Learning for Beginners in Python: Work On 12+ Projects

Password/解压密码0daydown

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