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aps0611

Config files for my GitHub profile.

atqf-workshop-2022-

A 5-day workshop starting from April 25 2022 and covers topics from the basics of finance to coding a trading strategy in python. The goal of this workshop is to give the students hands-on experience in developing a trading strategy and deploying it live along with an introduction to quantitative research. We expect that after this workshop students can explore these topics more on their own and contribute to the community.

awesome-notebooks

Ready to use data & AI templates, organized by tools to jumpstart your projects and data products in minutes. 😎 published by the Naas community.

awesome-public-datasets

A topic-centric list of HQ open datasets.

aws-deepracer-bootcamp

A hands on reinforcement machine learning bootcamp, created for Summer of Tech NZ. Designed to be run over a two hour session.

ba

Business Analytics using Python

backtesting_strategies

backtesting_strategies

bayesian-testing

AB Testing for data scientists

capegimini-data-hackathon

case_energy

Analysis

causalinference

On causal Inference

cpp

Everything CPP

cs-video-courses

List of Computer Science courses with video lectures.

data-science-for-beginners

10 Weeks, 20 Lessons, Data Science for All!

data_archive_kartik

Testing with this sample dataset

data_visualization

Data Visualization using Python

database_notes

This repository is collection of my SQL, MongoDB and other notes

dl

DeepLearning Notes

ds3_r_intro

Materials for the "Introduction to R Programming" workshop taught at the Hertie School Data Science Summer School (DS3)

dsa-for-sde-interview

This repository is aimed to contain all the questions required for SDE interview preparation from data structures and algorithms.

eda

firstcode

replit notebook

flask-api

This repository contains the Flask API's.

greenag_inclusivedatahackathon

hertieschoolsummerschool

Summer School Notes

introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

jan_term_2024

Repository contains the jan term resources

learn-algorithmic-trading

Learn Algorithmic Trading, Published by Packt

ml-admission-deploy

ml-for-beginners

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all