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DevelopmentData ScienceArtificial Intelligence

The Complete Course: Artificial Intelligence From Scratch

Learn the Essential Concepts of the AI like Neural Networks, Classification, Regression and Optimization Using Python.
Rating: 3.2 out of 53.2 (46 ratings)
2,544 students
Created by Sobhan N.
Last updated 12/2018
English
English [Auto]

What you'll 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).

Requirements

  • All you need is a decent PC/Laptop (2GHz CPU, 4GB RAM). You will get the rest from me.
  • You must know basic python programming.
  • Install Sublime and required library for python.
  • You should have a great desire to learn artificial intelligence and do it in a hands-on fashion.

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 Keras to forecast google stock price .  


  • you'll know how to use python and Keras to predict NASDAQ Index precisely.


  • you'll learn how to use python and Keras to forecast New York temperature with low error. 


  • you'll know how to use python and Keras to predict 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 deap to optimize simple function precisely.


  • you'll learn how to use python and deap to find optimum point of complicated Trigonometric function. 


  • you'll know how to use python and deap to solve  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 deap to optimize simple function precisely.


  • you'll learn how to use python and deap to find optimum point of complicated Trigonometric function. 


  • you'll know how to use python and deap to solve  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

Who this course is for:

  • Anyone who wants to make the right choice when starting to learn Artificial Intelligence.
  • Learners who want to work in data science and big data field
  • students who want to learn machine learning
  • Data analyser, Researcher, Engineers and Post Graduate Students

Instructor

Sobhan N.
AI Developer|Electrical Engineer (PhD)|21,000+ Students
Sobhan N.
  • 3.6 Instructor Rating
  • 446 Reviews
  • 22,155 Students
  • 15 Courses

My passion is teaching people through online courses. I love learning new skills, and since 2015 have been teaching people like you everything. I create courses that teach you how to become the better version of yourself with all kinds of skills.  

What would you like to learn?  

Would you like to learn Artificial Intelligence in python?  

Would you like to make money creating landing pages?  

Would you like to build your own AI programs & do something awesome for you?  

Would you like to learn Xamarin to make both iOS/Android apps?  

Would you like to learn how to write codes in HTML5 and CSS3?  

Would you like to learn MATLAB the scientific language for researchers?  

 

If you want to do any of these things, just enroll in the course. You have a 30-day money back guarantee if you don't like it. And I'm always improving my courses so that they stay up to date and the best that they can be. Check them out, and enroll today!  

__________________________________________________________________________  

About Sobhan N:   

I have PhD degree in Electrical Engineering and like to learn anything about Electronics, Programming and Artificial Intelligence. I like electronic stuff like Arduino, Raspberry Pi and microcontrollers.  

My passion is helping people reveal hidden talents and guide them into the world of startups and programming. I currently am teaching Artificial Intelligence, App Deign, Web Design and MATLAB programming languages. I’m also teaching Electrical Engineering and Computer Science Courses in Universities. 

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