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algorithmic-trading

This is code base for a trading robot using Zerodha Kite Connect API and python

algorithmic-trading-backtesting-in-python

Code snippet show casing backtesting a strategy in python on historical stock market data.

algorithmic-trading-backtesting-portfolio-of-stocks-python

This article describes how to test your algorithmic trading strategy on a portfolio of stocks. A portfolio reduces risk as opposed to just applying a strategy to a single stock. Optimizing the portfolio can result in higher returns and reduce overall risk (Increases Sharpe Ratio).

algorithmic-trading-backtesting-vwap-strategy

Ipython Notebook for backtesting VWAP strategy

algorithmic-trading-optimize-back-test

Code snippet describing optimization of back-testing strategies

av-jobathon-may-21

credit card lead prediction

backtesting-buy-low-sell-high

Backtesting a simple Buy Low Sell High Strategy

codeblocks-cplusplus-examples

collection of C++ example codes

codinginterviews

This repository contains coding interviews that I have encountered in company interviews

credit-card-lead-prediction

This repository showcases use of supervised machine learning approaches in identifying customers that could show higher intent towards a recommended credit card. Banks deploy such models to identify / classify and send targeted adds to potential customers and communicate through various means such as telecasting, e-mails, recommendations on net banking, mobile banking, etc.

data-structures-algorithms

Nothing is final, nothing is fatal. It all depends on how you roll...

dexter

GPT based Personalized AI assistant

diversified-stock-portfolio-using-clustering-analysis

This repository demonstrates application of unsupervised learning in the financial markets. K-Means clustering is employed to create a diversified portfolio of stocks and the resulting portfolio is backtesting against the S&P500 Index

fintech-constructing-a-alpha-model

This repository contains the code base for analyzing a portfolio of assets and creating a alpha model on historical finance data. Factors are constructed from OHLCV daily trading data, fundamental data and sentiments from twitter / news headlines. The alpha is then backtested to analyze its predictive power.

genai-llm-qna

LLM QnA using Langchain, Pinecone and OpenAI

generative-ai-for-beginners

18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

handle-vrep-python

VREP simulation of Handle (A simplified version of Boston Dynamics Robot HANDLE)

humanoid-bipedal-gait-design

This repository contains MATLAB supporting files for kinematic humanoid walk generation using linear oscillators

humanoid-matlab-gui

interactive-brokers-trading-bot

A Python library written to handle IB's Client Portal API, manage portfolio and execute trades.

kalman-filter-example

Uses Madgwick AHRS and Kalman Filter to fuse IMU and GPS data for trajectory Estimation from data collected from a rover. GPSIMUSensorFusion1.py (main script)

kinematics-robotic-arm

Forward and Inverse kinematics of 3 axis robotic arm

llm-frontend

frontend for llm applications

llmfrontend

frontend for llm application

mern-boilerplate

Contains boilerplate setup for frontend, backend, and cloud database and basic user auth

multiple-linear-regression-for-predicting-car-prices

The aim of this project is to develop a multi linear regression model for predicting car prices with the available independent variables. This will allow the management to understand how the prices will vary with the independent variables and allow them to manipulate the design of the cars and business strategy to meet certain price levels.

multiple-linear-regression-using-gradient-descent-on-seoul-bike-share-demand-data-set

This repository showcases multiple linear regression on the data set to predict the rented bike count. Exploratory data analysis is performed to give a deeper look into the data set. Gradient descent algorithm with the batch update is implemented to study the effects of the hyper parameters such as learning rate and threshold on the residuals, R - squared value, and nature of convergence on the test and training sets.

my-website

My Website

path-planning-algorithms-matlab

Collection of Path planning algorithms for autonomous navigation

path-planning-algorithms-python