Learn the Essential Concepts of the AI like Neural Networks, Classification, Regression and Optimization Using Python.

What you will learn

### Learn the basic of Artificial Intelligence from scratch.

### Learn how Neural Networks work.

### Program Multilayer Perceptron Network from scratch in python.

### You’ll know how recurrent neural networks work.

### You’ll learn how to create LSTM networks using python and Keras

### You’ll know how to forecast Google stock price with high accuracy

### Use k Nearest Neighbor classification method to classify datasets.

### Classify datasets by using Support Vector Machine method

### Understand main concept behind Support Vector Machine method.

### Classify Handwritten Images by Logistic classification method

### You’ll know how Linear Regression work.

### You’ll know how Multi Linear Regression work using sklearn and Python.

### Program Logistic Regression from scratch in python.

### Build Model to Predict CO2 and Global Temperature by Polynomial Regression.

### You’ll know the ideas behind Genetic Algorithm.

### You’ll know the ideas behind Particle Swarm Optimization Method.

### You’ll know how to find optimum point for complicated Trigonometric functions.

### You’ll learn how to solve well known problems like Travelling Salesman Problem (TSP).

Description

Do you like to learn how to **forecast economic time series** like stock price or indexes with high accuracy?

Do you like to know how to **predict weather** data like temperature and wind speed with a few lines of codes?

Do you like to classify Handwritten digits more accurately ?

If you say **Yes **so read more …

In computer science, **Artificial intelligence **(**AI**), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In this you are going to learn essential concepts of AI using Python:

Neural Networks

Classification Methods

Regression Analysis

Optimization Methods

_____________________________________________________________________________________________________________________

in the **First, Second,Third **sections you will learn Neural Networks

You will learn how to make Recurrent Neural Networks using Keras and LSTMs:

- you’ll learn how to use python and
**forecast google stock price**. - you’ll know how to use python and
**NASDAQ Index**precisely. - you’ll learn how to use python and
**forecast New York temperature**with low error. - you’ll know how to use python and
**New York Wind speed**accurately.

In the next section you learn how to use python and** sklearn** **MLPclassifier **to forecast output of different datasets like

**Logic Gates**

**Vehicles Datasets**

**Generated Datasets**

In the third section you can forecast output of different datasets using Keras library like

**Random datasets**

**Forecast International Airline passengers**

**Los Angeles temperature forecasting**

_____________________________________________________________________________________________________________________

Next you will learn how to classify well known datasets into with high accuracy using **k-Nearest Neighbors, Bayes, Support Vector Machine and Logistic Regression.**

In the **4th **section you learn how to use python and k-Nearest Neighbors to estimate output of your system. In this section you can classify:

**Python Dataset**

**IRIS Flowers**

**Make your own k Nearest Neighbors Algorithm**

In the **5th **section you learn how to use Bayes and python to classify output of your system with nonlinear structure .In this section you can classify:

**IRIS Flowers**

**Pima Indians Diabetes Database**

**Make your own Naive Bayes Algorithm**

You can also learn how to classify datasets by by **Support Vector Machines** to find the correct class for data and reduce error. Next you go further You will learn how to classify output of model by using **Logistic Regression**

In the **6th **section you learn how to use python to estimate output of your system. In this section you can estimate output of:

**Random dataset**

**IRIS Flowers**

**Handwritten Digits**

In the **7th** section you learn how to use python to classify output of your system with nonlinear structure .In this section you can estimate output of:

**Blobs**

**IRIS Flowers**

**Handwritten Digits**

_____________________________________________________________________________________________________________________

After it we are going to learn regression methods like **Linear, Multi-Linear and Polynomial Regression.**

In the **8th** section you learn how to use **Linear Regression** and python to estimate output of your system. In this section you can estimate output of:

**Random Number**

**Diabetes**

**Boston House Price**

**Built in Dataset**

In the **9th **section you learn how to use python and **Multi Linear Regression** to estimate output of your system with multivariable inputs.In this section you can estimate output of:

**Global Temprature**

**Total Sales of Advertising Campaign**

**Built in Dataset**

In the **10th **section you learn how to use python **Polynomial Regression** to estimate output of your system. In this section you can estimate output of:

**Nonlinear Sine Function**

**Python Dataset**

**Temperature and CO2**

Finally I want to learn you theory behind bio inspired algorithms like **Genetic Algorithm** and **Particle Swarm Optimization** Method. You’ll learn basic genetic operators like mutation crossover and selection and how they are work. You’ll learn basic concepts of **Particle Swarm** and how they are work.

In the 11th section you will learn how to use python and deap library to solve optimization problem and find **Min/Max points** for your desired functions using **Genetic Algorithm**.

- you’ll learn theory of
**Genetic Algorithm**Optimization Method - you’ll know how to use python and
**simple function**precisely. - you’ll learn how to use python and
**Trigonometric function**. - you’ll know how to use python and
**Travelling Salesman Problem (TSP)**accurately.

In the **12th **section we go further you will learn how to use python and deap library to solve optimization problem using **Particle Swarm Optimization**

- you’ll learn theory of
**Particle Swarm Optimization**Method - you’ll know how to use python and
**simple function**precisely. - you’ll learn how to use python and
**Trigonometric function**. - you’ll know how to use python and
**Rastrigin standard function**accurately.

___________________________________________________________________________

**Important information before you enroll:**

- In case you find the course useless for your career, don’t forget you are covered by a
**30 day money back guarantee, full refund, no questions asked!**

- Once enrolled, you have
**unlimited, lifetime access to the course!**

- You will have
**instant and free access to any updates**I’ll add to the course.

- You will give you
**my full support**regarding any issues or suggestions related to the course.

- Check out the curriculum and
**FREE PREVIEW lectures**for a quick insight.

**___________________________________________________________________________**

Music from Jukedeck – create your own at jukedeck com

___________________________________________________________________________

**It’s time to take Action!**

Click the “**Take This Course**” button at the top right now!

**.. .Don’t waste time! Every second of every day is valuable…**

I can’t wait to see you in the course!

Best Regrads,

Sobhan

Content