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ACA Machine Learning.md

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COMPETITIVE MACHINE LEARNING AND DATA ANALYTICS ACA PROJECT

MENTOR: SAYASH KAPOOR AND KSHITIJ PATEL

Our project was aimed at learning various Machine Learnign Algorithms, learning how to code these algorithms on Octave/Matlab and learning how various Machine Learning Systems work.

The project progressed mainly in following three phases:

  • Learning the basics and syntax of Matlab and Octave.
  • Completing the Machine Learnign course on Coursera by Andrew Ng.
  • Learning Scikit-learn library
  • Participating in competitions on Kaggle to apply what we have learnt.

Learning the basics of Octave and Matlab

  • Basic operations
  • Moving data around
  • Computing on data
  • Plotting the data
  • Control Statements, Vectorization

Completing the Machine Learning Course :

  • Learnt about Neural Networks, Support Vector Machines
  • Learnt about K-Means Clustering and Principal Component Analysis
  • Learnt about handling skewed data, optimizing these algorithms
  • Using machine learnign systems like Recommender Systems, Anomaly Detection Systems, Photo Optical Character Reader

Learning Scikit-Learn Library

  • Scikit-Learn is a machine learning library for python
  • Used Pandas library for preprocessign data and and other libraries to visualise the data
  • Used scikit-learn to run machine learning algorithms

Participating in competitions on Kaggle

  • Kaggle is a platform for predictive modelling and analytics competitions in which companies and researchers post data and statisticians and data miners compete to produce the best models for predicting and describing the data.
  • We participated in the introductory competitions on Kaggle (like Titanic) to apply whatever we learnt in the project in practical situations.

Made By Ajay Prakash Jalgaonkar (160059)