Omkar Pawaskar (OmkarPawaskar)

OmkarPawaskar

Geek Repo

Location:Mumbai/Bangalore

Github PK Tool:Github PK Tool

Omkar Pawaskar's repositories

Classification-of-Iris-flowers

My First Machine Learning Project . Based on Multi Class Classification of iris flowers

Language:PythonLicense:GPL-3.0Stargazers:2Issues:0Issues:0

MachineLearningPythonAndR

Implementation of different Machine Learning Algorithms or Models in Python and R

Language:PythonLicense:GPL-3.0Stargazers:1Issues:0Issues:0

Recommender

Build a recommendation engine using Django & a Machine Learning technique called Collaborative Filtering.

Language:PythonLicense:Apache-2.0Stargazers:1Issues:0Issues:0

Course-Certified-Solutions-Architect-Associate

AWS Certified Solutions Architect - Associate

Language:HTMLLicense:MITStargazers:0Issues:0Issues:0
Language:PythonLicense:Apache-2.0Stargazers:0Issues:0Issues:0
Language:Jupyter NotebookStargazers:0Issues:0Issues:0
Language:TeXStargazers:0Issues:0Issues:0
Stargazers:0Issues:0Issues:0
Language:PythonStargazers:0Issues:0Issues:0
Language:Jupyter NotebookStargazers:0Issues:0Issues:0

Video-Membership-Webapp

Building a membership application using FastAPI and a managed Cassandra database called AstraDB

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:0Issues:0Issues:0
Language:Jupyter NotebookStargazers:0Issues:0Issues:0
Language:PythonLicense:Apache-2.0Stargazers:0Issues:0Issues:0

Exploratory-Data-Analysis-Haberman-s-Cancer-Survival-Dataset

Haberman’s data set contains data from the study conducted in University of Chicago’s Billings Hospital between year 1958 to 1970 for the patients who undergone surgery of breast cancer. Source :https://www.kaggle.com/gilsousa/habermans-survival-data-set)

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:0Issues:1Issues:0

Fitnation

Side Project

Language:CSSStargazers:0Issues:0Issues:0

Home-Credit-Default-Risk

In this notebook, we will take an initial look at the Home Credit default risk machine learning competition currently hosted on Kaggle. The objective of this competition is to use historical loan application data to predict whether or not an applicant will be able to repay a loan.

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:0Issues:0Issues:0

Load-Prediction-Problem

Dream Housing Finance company deals in all home loans. They have presence across all urban, semi urban and rural areas. Customer first apply for home loan after that company validates the customer eligibility for loan. Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have given a problem to identify the customers segments, those are eligible for loan amount so that they can specifically target these customers.

Language:Jupyter NotebookStargazers:0Issues:0Issues:0

MachineLearningOctave

My Implementation of programming assignments for Coursera Machine Learning by Dr Andrew Ng

Language:MatlabStargazers:0Issues:0Issues:0
License:GPL-3.0Stargazers:0Issues:0Issues:0

py_fresh

Python Project Maker

License:MITStargazers:0Issues:0Issues:0
Language:PythonLicense:Apache-2.0Stargazers:0Issues:1Issues:0

REST-API-with-Flask-and-Python

Created REST API using Flask, Flask JWT, Flask RESTful, Flask SQLAlchemy

Language:PythonStargazers:0Issues:0Issues:0
Stargazers:0Issues:0Issues:0

Tic-Tac-Toe-using-ReactJS

Tic Tac Toe game implemented using ReactJS : Lets you play tic-tac-toe, Indicates when a player has won the game, Stores a game’s history as a game progresses, Allows players to review a game’s history and see previous versions of a game’s board.

Language:JavaScriptStargazers:0Issues:0Issues:0

Twitter-Sentiment-Analysis

Sentiment Analysis refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

Language:Jupyter NotebookLicense:GPL-3.0Stargazers:0Issues:0Issues:0
Language:PythonLicense:GPL-3.0Stargazers:0Issues:0Issues:0
Language:PythonLicense:GPL-3.0Stargazers:0Issues:0Issues:0