phuocchi's Stars
AbnerTeng/WorldQuant-Brain
RussellDash332/WQ-Brain
Simple API automation for submitting WorldQuant BRAIN alphas
WongKinYiu/yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
thinh-vu/vnstock
A powerful Python library for getting rich data from the Vietnam Stock Market using just a few lines of code
TheAlgorithms/Python
All Algorithms implemented in Python
karlosye/Quantitative-Financial-Data-Analysis-project
financial data analytics using statistical modelling and machine learning techniques
jjacks95/sentiment-analysis-financial-news
Capstone Project for Data Science Diploma at BrainStation
CodexploreRepo/CodexploreRepo
ashishpatel26/Titanic-Machine-Learning-from-Disaster
Start here if... You're new to data science and machine learning, or looking for a simple intro to the Kaggle prediction competitions. Competition Description The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy. Practice Skills Binary classification Python and R basics
instillai/machine-learning-course
:speech_balloon: Machine Learning Course with Python: