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tejasp12/README.md

Hi there 👋

Warm Welcome from Tejas...!

A place where you can find all the basics behind:

1. Regression Analysis:

 1.1.Linear
 
     1.1.1 Simple Linear Regression
     
     1.1.2 Multiple Linear Regression
 
 1.2 Logistic Regression
 
 1.3 Polynomial Regression
 
 1.4 Decision Tree and Random Forrest Regression
 
 1.5 Neural Network Regression

2. Classification Tasks:

 2.1 Decision Tree
 
 2.2 Random Forrest
 
 2.3 Naive Bays

3. Computer Vision:

 3.1 Image Classification
 
 3.2 Object Detection & Localization

Pinned

  1. Retail--Big-Mart_Sales_Analysis Retail--Big-Mart_Sales_Analysis Public

    Value to Business :: Using this Regression model, the decision-makers will able to understand the properties of various products and stores which play an important and key role in optimizing the Ma…

    Jupyter Notebook 2

  2. Entertainment--Movie_Rating_Prediction Entertainment--Movie_Rating_Prediction Public

    A combination of Data Science and Machine Learning techniques to predict ratings of a particular movie based on input features.

    HTML

  3. Government--Income_Level_Prediction Government--Income_Level_Prediction Public

    A Machine Learning Project for Prediction of the one's Income Level based on different features.

    HTML 1

  4. Improved_CV_with_Convolution_and_Pooling Improved_CV_with_Convolution_and_Pooling Public

    The project is the demonstration of building the Convolution Neural Network from scratch and compared its accuracy over simple Neural Network.

    Jupyter Notebook

  5. Computer_Vision-Classification-Identifying_Cats_Vs_Dogs Computer_Vision-Classification-Identifying_Cats_Vs_Dogs Public

    The project is the demonstration of building CNN for Identifying the Cat or Dog images.

    Jupyter Notebook 1

  6. Computer_Vision-Classification-Identifying_Horse_vs_Humans Computer_Vision-Classification-Identifying_Horse_vs_Humans Public

    The project is focused on building Classification Model using Convolution Neural Network for classifying the images into "Horse" and "Human".

    Jupyter Notebook