Cryptocurrency Trading With Machine Learning - Installation of Freqtrade & Neural Network Model

Greetings Viewers, Thank you for your interest in VishvaAlgo (Freqtrade Version), an advanced cutting-edge trading tool leveraging Machine Learning and Neural Networks for trading cryptocurrency assets across various platforms, including both Futures and Spot Trading. It comes with robust security features like stoploss, take profit, trailing stoploss, ROI-based returns, comprehensive risk management, customizable options, straightforward backtesting, dry-run/paper trading, live trading setup, seamless asset management, and much more. After many requests from other parts of the world where there is no access to Binance exchange, upon lot of deep research, was able to build upon freqtrade platform, which can be easily integrated with more than 100+ exchanges with simple 3-4 lines of providing exchange information in the config.json file. Unlike VishvaAlgo, individual configurations for stoploss, takeprofit, ROI, trailing stoploss, and leverage for each unique asset are not currently supported. However, through hyperopt optimization, we can determine the best common parameters such as leverage, stoploss, takeprofit, trailing stoploss, and ROI for the overall setup. Why Choose VishvaAlgo Freqtrade Version? - Advanced Machine Learning and Neural Network models Integration made easy for new/young Developers - Easy integration with 100+ exchanges via freqtrade - Optimized common parameters through hyperopt Unlike other platforms, VishvaAlgo Freqtrade Version focuses solely on freqtrade for its ease of use and extensive customization options. We believe this approach provides a more user-friendly experience, especially for new developers and traders. Trading With Machine Learning neural Networks VishvaAlgo Cryptocurrency - Installation of Packages - https://youtu.be/6v2Zw0KRK4o (Freqtrade Ver.) VishvaAlgo (for non Binance Exchange Traders) ML/AI - https://www.patreon.com/pppicasso/shop/freqtrade-ver-vishvaalgo-for-non-binance-180245 Patreon Link: https://www.patreon.com/pppicasso/shop Check Out Articles on Algorithm Trading and machine Learning Classification Models: https://medium.com/@imbuedeskpicasso Article on VIshvaAlgo v3.0 - https://imbuedeskpicasso.medium.com/vishvaalgo-v3-0-f4ca0facae7e Warm Regards, Puranam Pradeep Picasso Sharma Linkedin — https://www.linkedin.com/in/puranampradeeppicasso/ Patreon — https://patreon.com/pppicasso Facebook — https://www.facebook.com/puranam.p.picasso/ Twitter — https://twitter.com/picasso_999

Implementation of Machine Learning in Momentum Trading | Webinar

This comprehensive session explores the scenarios where machine learning seamlessly integrates into momentum trading practices. Delve into various types of momentum trading strategies, understand the necessity and effectiveness of machine learning in this domain, and explore practical applications. We'll walk you through implementing ML-based classifiers and clustering algorithms with practical examples, unlocking the vast potential of machine learning in momentum trading. ******** Build your skills and learn the application of machine learning for enhancing momentum trading strategies. Explain how to use ML classification to predict momentum and craft a time-series momentum strategy. Check it out👉 https://bit.ly/3Jj1jWU Connect with us Today👉 ******** About The Speaker: Varun Kumar Pothula (Quantitative Analyst at QuantInsti) Varun holds a Masters degree in Financial Engineering. He has experience working as a trader, a global macro analyst, and algo trading strategist. Currently, working in the Content & Research Team at QuantInsti as a Quantitative Analyst, his contributions help in creating offerings for learners in the domain of algorithmic & quantitative trading. Overview: - Types of momentum trading approaches - A look into traditional and advanced time series momentum trading approaches - Need for ML in momentum trading - Implementing machine learning for trading time series momentum - Improving ML models used for momentum trading - Risk management using ML - Traditional cross- sectional momentum trading approach - Implementing machine learning to trade cross- sectional momentum - Interactive Q&A Pre-Requisites: - A fundamental understanding of trading terminology. - Basic familiarity with machine learning concepts. Who Should Attend? Traders, Financial Analysts, Quantitative Analysts, Algorithmic Traders, Financial Engineers, Students, Researchers, and anyone interested in the financial markets. ******** Learning Resources: Learning Track: Machine Learning & Deep Learning in Trading I - https://bit.ly/4aNs81m Learning Track: Machine Learning & Deep Learning in Trading II - https://bit.ly/4d0iaLW FREE Ebooks: 🎁Machine Learning In Trading | Step By Step Implementation of ML Models - https://bit.ly/3SXt7Ww 🎁Algorithmic Trading | A Rought & Ready Guide - https://bit.ly/48n9b3E 🎁Python Basics | With Illustrations From The Financial Markets - https://bit.ly/48hqCCW ----------------------------------------- 🔔 Subscribe to our channel for more Algorithmic Trading tutorials and tips! 👍 Like this video and share it with your fellow traders. 💬 Drop your questions and comments below. We'd love to hear from you! ----------------------------------------- #QuantInsti #Quantra #AlgorithmicTrading #AlgoTrading #MomentumTrading #MachineLearning #ML #MachineLearningInrading