/Intro_To_Hands-On-Machine-Learning-Using-Python

This repository contains the iPython notebook files corresponding to my hands-on tutorial sessions at the "7-days Hands On Machine Learning Using Python" workshop(TEQIP-Funded) at GUIST, Guwahati University, held on 16-22 Aug. 2020.

Primary LanguageJupyter Notebook

Introduction To Hands-On Machine Learning Using Python

This repository contains the iPython notebook files corresponding to my practical sessions at the "7-days Hands On Machine Learning Using Python" workshop(TEQIP-Funded) at GUIST, Guwahati University, held on 16-22 Aug. 2020.

As part of this workshop, I served as the sole resource person for the hands-on sessions, which covered the following topics-

  1. Topic 0.1: Python Basics
  2. Topic 0.2: Numpy Basics
  3. Topic 0.3: Pandas Basics
  4. Topic 1: Exploratory data analysis for diabetes prediction.
  5. Topic 2: Exploratory data analysis for breast cancer prediction.
  6. Topic 4: Clustering using K-Means.
  7. Topic 5: Traditional Machine Learning based classification of medical imaging data.
  8. Topic 6: Traditional Machine Learning based text classification.
  9. Topic 7: Deep Neural Networks based breast cancer prediction.
  10. Topic 8: Convolutional Neural Network based handwritten digit recognition.
  11. Topic 9: Convolutional Neural Network based classification of medical image data.
  12. Topic 10: Text Sentiment analysis using LSTM based RNN.

Corresponding to each of the topic mentioned above, iPython notebooks have been uploaded in this repository.

Datasets utilized in this workshop are-

  1. PIMA Indian diabetes dataset. (https://www.kaggle.com/uciml/pima-indians-diabetes-database)
  2. Breast Cancer Wisconsin (Diagnostic) Dataset. (https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic))
  3. Breast Cancer Coimbra Dataset. (https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Coimbra)
  4. MNIST dataset. (http://yann.lecun.com/exdb/mnist/)
  5. IMDB Movie Review dataset. (https://ai.stanford.edu/~amaas/data/sentiment/)
  6. Breast Ultrasound Image dataset. (https://data.mendeley.com/datasets/wmy84gzngw/1)