The Complete Course: Artificial Intelligence From Scratch
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- Curriculum
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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
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in the First, Second,Third sections you will learn Neural Networks
You will learn how to make Recurrent Neural Networks using Keras and LSTMs:
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you’ll learn how to use python and Keras to forecast google stock price .
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you’ll know how to use python and Keras to predict NASDAQ Index precisely.
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you’ll learn how to use python and Keras to forecast New York temperature with low error.
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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
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Logic Gates
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Vehicles Datasets
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Generated Datasets
In the third section you can forecast output of different datasets using Keras library like
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Random datasets
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Forecast International Airline passengers
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Los Angeles temperature forecasting
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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:
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Python Dataset
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IRIS Flowers
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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:
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IRIS Flowers
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Pima Indians Diabetes Database
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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:
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Random dataset
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IRIS Flowers
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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:
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Blobs
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IRIS Flowers
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Handwritten Digits
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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:
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Random Number
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Diabetes
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Boston House Price
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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:
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Global Temprature
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Total Sales of Advertising Campaign
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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:
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Nonlinear Sine Function
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Python Dataset
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Temperature and CO2
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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.
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you’ll learn theory of Genetic Algorithm Optimization Method
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you’ll know how to use python and deap to optimize simple function precisely.
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you’ll learn how to use python and deap to find optimum point of complicated Trigonometric function.
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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
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you’ll learn theory of Particle Swarm Optimization Method
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you’ll know how to use python and deap to optimize simple function precisely.
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you’ll learn how to use python and deap to find optimum point of complicated Trigonometric function.
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you’ll know how to use python and deap to solve Rastrigin standard function accurately.
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Important information before you enroll:
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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!
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Once enrolled, you have unlimited, lifetime access to the course!
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You will have instant and free access to any updates I’ll add to the course.
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You will give you my full support regarding any issues or suggestions related to the course.
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Check out the curriculum and FREE PREVIEW lectures for a quick insight.
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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
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2Recurrent neural networks and LSTMs theoryVideo lesson
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3Required Softwares and LibrariesText lesson
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4Predict Google stock price using LSTMs - Part1Video lesson
Learn how to Predict Google stock price using LSTMs
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5Predict Google stock price using LSTMs - Part2Video lesson
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6Predict Google stock price using LSTMs - Part3Video lesson
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7Predict Google stock price using LSTMs - Part4Video lesson
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8Predict Google stock price using LSTMs - Part5Video lesson
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9Source CodeText lesson
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10Forecast NASDAQ Index using LSTMs and Keras library - Part 1Video lesson
Learn How to Forecast NASDAQ Index using LSTMs and Keras library accurately
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11Forecast NASDAQ Index using LSTMs and Keras library - Part 2Video lesson
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12Forecast NASDAQ Index using LSTMs and Keras library - Part 3Video lesson
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13Forecast NASDAQ Index using LSTMs and Keras library - Part 4Video lesson
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14Forecast NASDAQ Index using LSTMs and Keras library - Part 5Video lesson
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15Source CodeText lesson
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16Predict New York annual temperature using LSTMs - Part 1Video lesson
Learn how to Predict New York annual temperature using LSTMs
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17Predict New York annual temperature using LSTMs - Part 2Video lesson
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18Predict New York annual temperature using LSTMs - Part 3Video lesson
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19Predict New York annual temperature using LSTMs - Part 4Video lesson
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20Predict New York annual temperature using LSTMs - Part 5Video lesson
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21Source CodeText lesson
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22Forecast New York wind speed using LSTMs and Keras library - Part 1Video lesson
In this lecture you will learn How to Forecast New York wind speed using LSTMs and Keras library
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23Forecast New York wind speed using LSTMs and Keras library - Part 2Video lesson
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24Forecast New York wind speed using LSTMs and Keras library - Part 3Video lesson
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25Forecast New York wind speed using LSTMs and Keras library - Part 4Video lesson
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26Forecast New York wind speed using LSTMs and Keras library - Part 5Video lesson
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27Source CodeText lesson
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28Recurrent Neural Networks and LSTMs QuizQuiz
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29Recurrent Neural Networks and LSTMs AssignmentText lesson
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30Theory of MLP Neural NetworksVideo lesson
In this lecture you will learn Multi Layer Perceptron Neural Networks Theory
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31Required Softwares and LibrariesText lesson
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32Make MLP neural network to create Logic GatesVideo lesson
In this Lecture You Will learn How to Make MLP neural network to create Logic Gates
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33Source CodeText lesson
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34Using MLP to Detect Vehicles Precisely Part 1Video lesson
In this we make program to detect vehicle types correctly.
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35Using MLP to Detect Vehicles Precisely Part 2Video lesson
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36Source CodeText lesson
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37Classify random data using Multilayer Perceptron Part 1Video lesson
In this Lecture You will learn how to Classify random data using Multilayer Perceptron
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38Classify random data using Multilayer Perceptron Part 2Video lesson
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39Source CodeText lesson
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40Using Keras to forecast 1000 data with 100 features in a few seconds Part 1Video lesson
In this Lecture you are going to learn how to Use Keras to forecast 1000 data with 100 features in a few seconds
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41Using Keras to forecast 1000 data with 100 features in a few seconds Part 2Video lesson
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42Source CodeText lesson
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43Forecasting international airline passengers using keras Part1Video lesson
using keras to Forecast international airline passengers correctly
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44Forecasting international airline passengers using keras Part2Video lesson
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45Source CodeText lesson
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46Los Angeles Temperature Forecasting Part 1Video lesson
In this lecture you will learn how to use MLP for Los Angeles Temperature Forecasting
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47Los Angeles Temperature Forecasting Part 2Video lesson
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48Los Angeles Temperature Forecasting Part 3Video lesson
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49Source CodeText lesson
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50Multilayer Perceptron Neural Networks QuizQuiz
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51Multilayer Perceptron Neural Networks assignmentText lesson
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52Theory of k Nearest Neighbors Classification MethodVideo lesson
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53Required Softwares and LibrariesText lesson
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54Use k Nearest Neighbors Classification Method to classify random dataset Part 1Video lesson
In this lecture we Use the power k Nearest Neighbors Classification Method to classify random dataset accurately.
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55Use k Nearest Neighbors Classification Method to classify random dataset Part 2Video lesson
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56Source CodeText lesson
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57Learn How to Use k Nearest Neighbors Classification for IRIS DatasetVideo lesson
In this lecture you will Learn How to Use k Nearest Neighbors Classification for IRIS Dataset. The IRIS dataset is the most famous benchmark for classification problems.
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58Source CodeText lesson
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59Write k Nearest Neighbors Classification Method by yourself Part 1Video lesson
Learn how to Write k Nearest Neighbors Classification Method by yourself.
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60Write k Nearest Neighbors Classification Method by yourself Part 2Video lesson
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61Source CodeText lesson
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62k Nearest Neighbors Classification Method QiuzQuiz
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63k Nearest Neighbors Classification Method AssignmentText lesson
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64Theory of Naive Bayes Classification MethodVideo lesson
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65Use the power of Naive Bayes to Classify IRIS Dataset Part 1Video lesson
Learn how to Use Naive Bayes to Classify IRIS Dataset accurately.
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66Use the power of Naive Bayes to Classify IRIS Dataset Part 2Video lesson
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67Source CodeText lesson
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68Learn how to Use Naive Bayes to Classify Diabetes datasetVideo lesson
In this lecture you are going to Learn how to Use Naive Bayes to Classify Diabetes dataset. You also have access to dataset and source code in the next lecture.
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69Source CodeText lesson
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70Write Naive Bayes Classification Method by Yourself Part 1Video lesson
In this lecture you will learn how to Write Naive Bayes Classification Method by Yourself. Then you are able to predict gender of human.
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71Write Naive Bayes Classification Method by Yourself Part 2Video lesson
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72Source CodeText lesson
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73Naive Bayes Classification Method QuizQuiz
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74Naive Bayes Classification Method AssignmentText lesson
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75Theory of Support Vector Machine Classification MethodVideo lesson
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76Support Vector Machine Classification Method for two classes datasetVideo lesson
IN this lecture you will learn how to use Support Vector Machine Classification Method to classify two classes dataset
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77Source CodeText lesson
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78Use the Power of Support Vector Machine Method for IRIS dataset Part 1Video lesson
Use the Power of Support Vector Machine Method for IRIS dataset classification based on 4 features of this flower.
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79Use the Power of Support Vector Machine Method for IRIS dataset Part 2Video lesson
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80Source CodeText lesson
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81Use Support Vector Machine for Hand Written Images Classification Part 1Video lesson
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82Use Support Vector Machine for Hand Written Images Classification Part 2Video lesson
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83Source CodeText lesson
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