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cohort_analysis

crossvalidation-linear-regression

This notebook demonstrates how to do cross-validation (CV) with linear regression as an example (it is heavily used in almost all modelling techniques such as decision trees, SVM etc.). We will mainly use sklearn to do cross-validation.

data-science-complete-tutorial

For extensive instructor led learning

data-visualisation

In this section, we will see how to: Visualise univariate distributions Visualise bivariate distributions We will also start using the seaborn library for data visualisation. Seaborn is a python library built on top of matplotlib. It creates much more attractive plots than matplotlib, and is often more concise than matplotlib when you want to customize your plots, add colors, grids etc.

django-ecommerce

An e-commerce website built with Django

ecommerce

We're going to take you step-by-step to build a modern, fully open-source, eCommerce web application using Python, Django, Bootstrap, Javascript, and more.

export_and_import_data_from_mongodb_usnig_python

Export your CSV file to Mongo Db with this Python Code in jupyter notebook.

fictional-octo-goggles

gradient-descent

In this Python notebook we will go through an example of implementing Gradient Descent in simple and multiple linear regression, for this we will be using housing dataset.

hindustan-unilever-stock-prediction

knn

K-Nearest Neighbors (KNN) is one of the simplest algorithms used in Machine Learning for regression and classification problem. KNN algorithms use data and classify new data points based on similarity measures. The data is assigned to the class which has the nearest neighbors.

machine-learning-using-pyspark

Learn Machine Learning using PySpark from scratch

media-company-case-study

Problem Statement: A digital media company (similar to Voot, Hotstar, Netflix, etc.) had launched a show. Initially, the show got a good response, but then witnessed a decline in viewership. The company wants to figure out what went wrong.

multiple-linear-regression

Multiple linear regression (MLR), also known simply as multiple regression, is a statistical technique that uses several explanatory variables to predict the outcome of a response variable. The goal of multiple linear regression (MLR) is to model the linear relationship between the explanatory (independent) variables and response (dependent) variable.

numpy

Numpy is the most used Python libraries for data science. NumPy consists of a powerful data structure called multidimensional arrays.

pandas

Pandas is powerful Python library that provides fast and easy data analysis platform.

porto_seguro

Codes for Kaggle's Porto Seguro claim prediction competition. The k-fold model scores .285 Gini on the public lederboard

pyspark-learning

Updated repository

simple-linear-regression

In this notebook, we'll build a linear regression model to predict 'Sales' using 'TV' as the predictor variable.

tensorflow

Understanding TensorFlow from scratch