Shikhar Saxena's Projects
A curated list of references for MLOps
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Data Analysis and Visualization of Data Breach from 2004 to 2021
Develop production ready deep learning code, deploy it and scale it
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
For the purpose of Mozilla Bhubaneswar Open Source Session.
This project's aim is to measure the popularity of each league using the search data collected from Google Trends, which gives real-time historical data on search words. With this project, it is also possible to compare and forecast how the sports league are trending with respect to each other using five models — Holt-Winters Multiplicative (HWMM), Naive method, simple avg, Holt's Linear method, and Seasonal Autoregressive Integrated Moving Average (SARIMA). Businesses interested in advertising or investing with either league may leverage these forecasts for deciding which sports league provides the greater or long-term value.
Task 1 sparks foundation internship tasks
From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
As a business manager, try to find out the weak areas where you can work to make more profit.
AIM: As a security/defense analyst, try to find out the hot zone of terrorism.
An Open Source Machine Learning Framework for Everyone
As a sports analysts, find out the most successful teams, players and factors contributing win or loss of a team.
Create the Decision Tree classifier and visualize it graphically on given Iris dataset.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent