Deepak Rai's Projects
Learning Machine Learning and showcasing my work for 100 Days.
My learning about various Statistical Learning methods and it's implementation using R or Python.
Example š Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using š§ Amazon SageMaker.
Applied ai course is a online platform to learn about data science. In this repository include assignments ,projects, coding etc. done in the course
š Papers & articles of companies sharing their work on applied data science & machine learning.
Repo for 5th place solution for WNS Hackathon on AnalyticsVidhya
:memo: An awesome Data Science repository to learn and apply for real world problems.
A curated list of awesome Deep Learning tutorials, projects and communities.
A curated list of awesome machine learning interpretability resources.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
A topic-centric list of high-quality open datasets in public domains. By everyone, for everyone!
A curated list of awesome Python frameworks, libraries, software and resources
Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/
The objective of this project is to predication of bike rental count
The objective of this case is to predict the whether the customer will churn or not.
Welcome to the one point community-driven encyclopedia for anything in technology.
Repo of data science coding challenges for various companies
We use Python to get intuition on complex concepts, empirically test theoretical proofs, or build algorithms from scratch
This repo contains some R learning activities we created for the course I for the ColumbiaX series on Data Science and Analytics on edX.
This is a course provided by Coursera
Lectures for Udemy - Complete Python Bootcamp Course
:mortar_board: Path to a free self-taught education in Computer Science!
Computer Vision Intro OpenCV 3 in Python & Machine Learning - University of Edinberg
The CQF program
Modeled the credit risk associated with consumer loans. Performed exploratory data analysis (EDA), preprocessing of continuous and discrete variables using various techniques depending on the feature. Checked for missing values and cleaned the data. Built the probability of default model using Logistic Regression. Visualized all the results. Comput
In 2019, more than 19 million Americans had at least one unsecured personal loan. Personal lending is growing at an extremely fast rate, and FinTech firms need to go through an organize large amounts of data in order to optimize lending. Python will be used to evaluate several machine learning models to predict credit risk. Algorithms such as Rando
List of Computer Science courses with video lectures.
General Assembly's Data Science course in Washington, DC
Code for Data Pipelines with Apache Airflow