Shanmugasundaram M's repositories
a_little_book_of_python_for_multivariate_analysis
A Little Book of Python for Multivariate Analysis
algorithms_in_ipython_notebooks
A repository with IPython notebooks of algorithms implemented in Python.
big_data_for_chimps
A Seriously Fun guide to Big Data Analytics in Practice
confusion_matrix
Code used to understand the confusion matrix.
customer_segments
The Principal Component Analysis (PCA) is implemented on a dataset (from 440 clients of a wholesale distributor with variables related to its clients' total spending values on different product categories) and the first principal components are used to cluster the clients into an optimal number of segments. Useful information is derived from segments that will help the wholesale distributor to assess changes to services via A/B testing on every segment.
Default_Loan_Prediction
Code for Kaggle's Default Loan Prediction - Imperial College London challenge.
Energy-Disaggregation-Product-PoC-kaggle-competition
Energy Disaggregation Product Proof-of-Concept Using Data Science to Develop a New Product
Exploratory_Data_Analysis_Visualization_Python
Data analysis and visualization with PyData ecosystem: Pandas, Matplotlib Numpy, and Seaborn
Heart-disease-prediction-system-in-python-using-Support-vector-machine-and-PCA
Predicts the Probability of Heart Disease in a person given the patients' medical details . Dimensionality Reduction is performed using Principal Component Analysis and Classifier used is SVM and LinearSVC
knowledge_representation_pytorch
Several knowledge graph representation algorithms implemented with pytorch
Loan-Defaulter-Prediction-Machine-Learning
Prediction of loan defaulter based on more than 5L records using Python, Numpy, Pandas and XGBoost
Loan_Default_Prediction
This is the Python Code for the submission to Kaggle's Loan Default Prediction by the ID "HelloWorld"
machine-learning
Content for Udacity's Machine Learning curriculum
Machine-Learning-2
Home made machine learning receipes
machine-learning-dataschool
Detailed notes and code to learn the basics of machine learning with scikit-learn.
machine_learning_techniques
In which I implement some applications of machine learning techniques.
Maths-for-Data-Science-Machine-Learning
Statistics, Linear Algebra basics
MNIST-K-Means-Clustering
K-Means Clustering to Identify Handwritten Digits
PredictiveModeling_withPython
Notebooks for the Course
rasbt-python-machine-learning-book
https://github.com/rasbt/python-machine-learning-book
Retinet
A CNN to classify Diabetic Retinopathy with Fundus images
RoCA
Root Cause Analysis in IT Landscapes using Markov Logic Networks