mazsoltani/Machine-Learning-1

Machine-Learning

Assignment 31

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• Implement and practice the following tutorials on the w3schools website:
  • 1- Matplotlib
  • 2- Machine Learning

Assignment 32

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1- Python for Data Science Certificate (Sololearn)

2- Fruits Visualization (banana vs apple)

• python visualization (case) fruit classification (banana and Apple war)

3- Melons VS balloons (3dscatter)

• Create a database with random numbers for (balloon and melon)
• Display the generated database in three dimensions (3D Scatter)

Assignment 33

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• Analysis an Online Retail dataset to figure out the problem in April.
• As shown in the charts, in April, the store was unable to attract new customers as well as retain old customers.

  

Assignment 34

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1- Covid-19

• Analyze Covid 19 data and show the 8 most affected countries in April 2020

  

• Draw a graph that shows the mortality rate VS the number of cases in Iran on different days

  

2- KNN

• Implement a method called evaluate in the KNN algorithm class.It should Returns the accuracy percentage of the algorithm as a number between zero and one.

3- KNN-OCR of Hand-written Digits

• KNN-OCR of Hand-written Digits

Assignment 35

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1- iris-KNN

• Run the KNN algorithm on the iris database with different K value and Draw the obtained accuracy together as a graph

  

2- Abalone-KNN

• Run the KNN algorithm on the Abalone database

Nemo-KNN

• Use KNN algorithm and Train the algorithm with a Clownfish image and test it with another Clownfish image

Assignment 36

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1- iris-KNN-Confusion Matrix

• For the iris dataset, plot the confusion matrix
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2- LLS- Study hour & Score

• Create continuous random data on the number of study hours (X) and the score (Y) of students as follows (the more you study, the higher your score)

  

• Then draw a few lines with a random and wrong slope on it. Then, with the help of the Linear least squares method, get and draw the line with the correct slope.

  

• Compare the output of your method with the output of the linregress method from the scipy library

  

3- Boston LLS Regression

• Implement the Linear least squares method on the Boston database from the scikit-learn library

  

Assignment 37

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1- Digikala

• Draw the following diagrams for Digikala data:
  • Number of orders per month
  • Customers by city
• Result

  

2- QR Code Reader

• Qr Code Reader program using opencv.

3- Abalone LLS

• Solve the Abalone problem as Regression and estimate the age of the oyster
• Add 4 Loss function :
  • MAE Loss
  • MSE Loss
  • Huber Loss
  • Hinge Loss

Assignment 38

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• Use the perceptron algorithm to teach a linear model on the Boston dataset
  • Data graph and forecast page in animation and Graph the error rate in the training process

    

  • Write the predict function that can take x_test to predict y_test.
  • Write the evaluate function and report the train accuracy and test accuracy.

Assignment 39

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Weather Temp Prediction

• This is not a linear problem, so we will not get the ideal answer with a linear method, I will soon learn a way to solve this problem correctly
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Assignment 40

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Titanic Prediction with MLP, Perceptron, KNN

• Use machine learning to create a model that can predict survivors of the Titanic

  • Execute predict on test data and report results
  • Save MLP model
  • Compare the accuracy of the models

• Accuracy compare on Test data

  • Algorithm	KNN	Perceptron	MLP (Multi Layer Perceptron)
    Accuracy	80 %	66 % (r2 squared)	93 %

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Assignment 41

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MLP_Boston Housing

• Use the MLP (Multi Layer Perceptron) model on the Boston dataset
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MLP_Weather Temp Prediction

• solve Assignment 39 with a MLP model

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• Accuracy ( Loss ) compare on Test data

  • Algorithm	MLP (Multi Layer Perceptron)	Perceptron
    Accuracy ( Loss )	2.95	7.46