Table of Contents

## Introduction:-

**Deep learning Machine Learning with python** .Deep Learning is a technology of Machine learning that teaches and gives the command to the computer to do that work that comes directly from the human side. It is the data science important element. Which includes the modeling of the statistics and predictive.

In Deep Learning, Deep means adding additional layers to the data.

Machine Learning means performing several task computer learning from the data.

## Details about the Deep Learning and Machine Learning:-

Download the advanced Features of Deep Learning using the programming language of Python by Francois for free. The Pdf of Deep Learning is also available. Learn the step-by-step process of Deep Learning. Deep Learning is a very important language for learning, for those who want to make a carrier in the field of Deep Learning. For the developers, Notes of Deep Learning are available.

### Some of the topics are also learned inside Deep Learning and Machine Learning-

- Learn the Artificial Intelligence
- Understand the Machine Learning
- Understand the Deep Learning
- Brief history of the Machine Learning
- Why did we choose Deep Learning

## The mathematical blocks of Neutral network building:-

Some of the building blocks of the neural network are mentioned below in the following points-

Firstly, look after the neural network

The representations of data of the neural network

Neural network gears- operation of tensor

Neural network engine- optimization based on gradient

Lastly, look at the first topic of neural networks and its example.

## The topics related to the neural network:-

- Neural network anatomy
- Explain the introduction of Keras 61 Keras, Tensorflow, Theano, and CNTK
- Setting the workstation of Deep Learning
- Reviews on classifying movie- example of a binary classification
- Classifying the newswires- classification of multiple
- Predicting the prices of the house- an example of regression

## The Fundamental of machine learning:-

- Understand the branches of Machine Learning-
- The four branches of Machine Learning
- Evaluating the models of Machine Learning
- Pre-Processing data
- Engineering feature
- Learning feature

## The Practice of Deep Learning:-

#### Computer vision for Deep Learning:-

- Convents introduction
- Training from scratch to a convent on a small
- P retrained convent using Deep Learning
- Visualizing what we learn in the convent

#### Text and Sequence of Deep Learning:-

- Working with the data of the text
- Understanding what is a recurrent neural network
- Uses of recurrent neural network in advance
- Understand the processing of sequence with convent

#### Best practices of Deep Learning in advance:-

- The model of sequential which is going beyond- the API function of Keras
- The model of Deep Learning inspecting and monitoring by Keras and Tensor board
- Getting the most models out of it

#### The generative of Deep Learning:-

- Generation of text with LSTM
- Implementing the Deep Learning in Keras
- Transfer of neural style
- Images generated with the autoencoders of variational
- Explain the introduction of a generative network of adversarial

## Conclusion:-

The short explanation of Deep Learning and Machine learning and their features. The key concepts of the review of Deep Learning and Machine Learning.

The limitation of Deep Learning. What is the goal of Deep Learning in the future? The first and rapidly moving field in the present world, Deep Learning is also staying up to date according to the firstly going world.