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This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates

License: MIT License

Python 0.44% R 0.07% Jupyter Notebook 99.48% HTML 0.01%
machine-learning algorithm nlp-machine-learning prediction-model datascience linear-regression logisitic-regression polynomial-regression random-forest-regression decision-tree-regression

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machine-learning's Issues

Implement different ML algorithms with open source data files

  1. Star it
  2. Fork the repo
  3. Clone it onto your PC.
  4. Create a folder with your GitHub username
  5. Create separate files for all the issues you are solving and always open an issue which has all details of the process or method you will use to perform anomaly detection and wait till it is assigned (not more than 2-3 hours it will take, we are passionate open source developers )
  6. Open PRs for the issues you are solving. (You can open multiple PRs for different issues by branching).

Note: Don't upload zip , please upload in a separate folder and we request to follow the given instructions in the repository

Implement different ML algorithms with open source data files

  1. Star it
  2. Fork the repo
  3. Clone it onto your PC.
  4. Create a folder with your GitHub username
  5. Create separate files for all the issues you are solving and always open an issue which has all details of the process or method you will use to perform anomaly detection and wait till it is assigned (not more than 2-3 hours it will take, we are passionate open source developers )
  6. Open PRs for the issues you are solving. (You can open multiple PRs for different issues by branching).

Note: Don't upload zip , please upload in a separate folder and we request to follow the given instructions in the repository

Implement different ML algorithms with open source data files

  1. Star it

  2. Fork the repo

  3. Clone it onto your PC.

  4. Create a folder with your GitHub username

  5. Create separate files for all the issues you are solving and always open an issue that has all details of the process or method you will use to perform anomaly detection and wait till it is assigned (not more than 2-3 hours it will take, we are passionate open source developers )

  6. Open PRs for the issues you are solving. (You can open multiple PRs for different issues by branching).

  7. Make sure the data is only from the given category (No repetitions of same data )

           a. Healthcare -covid, heart attack, cancer, etc
           
           b. Finance -stocks etc
           
           c. Retail or CPG
           
           d. Image classifciation
           
           e. Time series
    

Only code like .py are not accepted please push proper jupyter (.ipynb) files with problem statement and solution analysis.

Note: Don't upload zip , please upload in a separate folder and we request to follow the given instructions in the repository

Apriori Algorithm

I want to add a Jupyter Notebook containing an Introduction, explanation, EDA and model of the algorithm. Please assign me this issue.
@eaglewarrior

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