jakevdp /
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
99/100 healthLoading repository data…
PacktPublishing / repository
No description provided.
A transparent discovery signal based on current public GitHub metadata.
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
This is the code repository for Machine Learning for Algorithmic Trading Bots with Python [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Have you ever wondered how the Stock Market, Forex, Cryptocurrency and Online Trading works? Have you ever wanted to become a rich trader having your computers work and make money for you while you’re away for a trip in the Maldives? Ever wanted to land a decent job in a brokerage, bank, or any other prestigious financial institution?We have compiled this course for you in order to seize your moment and land your dream job in financial sector. This course covers the advances in the techniques developed for algorithmic trading and financial analysis based on the recent breakthroughs in machine learning. We leverage the classic techniques widely used and applied by financial data scientists to equip you with the necessary concepts and modern tools to reach a common ground with financial professionals and conquer your next interview.By the end of the course, you will gain a solid understanding of financial terminology and methodology and a hands-on experience in designing and building financial machine learning models. You will be able to evaluate and validate different algorithmic trading strategies. We have a dedicated section to backtesting which is the holy grail of algorithmic trading and is an essential key to successful deployment of reliable algorithms.
The code bundle for this video course is available at - https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-Python
To fully benefit from the coverage included in this course, you will need: This course is compiled for data science beginners and professionals who want to shift their career to financial sector. This course assumes a basic knowledge of Python programming such as conditional and looping statements. The course is self contained in terms of the concepts, theories, and technologies it requires to build trading bots.
This course has the following software requirements: Eclipse Photon with PyDev Plugin, Latest Version Anaconda platform Google Chrome
Selected from shared topics, language and repository description—not editorial ratings.
jakevdp /
Python Data Science Handbook: full text in Jupyter Notebooks
99/100 healthfastai /
The fastai book, published as Jupyter Notebooks
85/100 healthfchollet /
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
80/100 healthipython /
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
90/100 healthkubeflow /
Machine Learning Toolkit for Kubernetes
96/100 health