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machine-learning-algorithms

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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abhinand5
abhinand5 commented Oct 10, 2020

Implementation of Basic ML stuff (from scratch or without extensive use of higher-level functions)

Description

If you think you can write notebook/scripts that can vastly help beginners understand the ins outs of the chosen ML algorithm/problem. Please go ahead and reply in this thread.

Instructions

  • Use Python
  • Don't make a pull request unless you are assigned with the task.

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

  • Updated Jul 2, 2019
  • Jupyter Notebook

The overall objective of this toolkit is to provide and offer a free collection of data analysis and machine learning that is specifically suited for doing data science. Its purpose is to get you started in a matter of minutes. You can run this collections either in Jupyter notebook or python alone.

  • Updated Jan 14, 2018
  • Jupyter Notebook

I have tried to predict the survival of passengers on the Titanic using various techniques and machine learning algorithms. This is currently a on-going competition on Kaggle and I have got a best score of 0.83253 (top 2%) out of 11262 teams. I will be making modifications to improve the score.

  • Updated May 12, 2018
  • Jupyter Notebook
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