Mtemi

autobot

for abc

Binance-Futures-and-Crypto-Profiles-Algorithm-

A web-based solution that helps a user to manage and optimize their portfolio of cryptocurrencies according to certain criteria. You set how the distribution within the portfolio should change according to how the price of bitcoin changes. This way you can know how much you hold and in what positions; of crypto in various platforms; just on one platform. The algorithm helps you adjust various positions of crypto held in several platforms based on how Bitcoin varies thus advising you whether to buy or sale.

binance.py

A python3 binance API (v3) wrapper powered by modern technologies such as asyncio. The project aims to rival python-binance.

Bybit-Trading-Bot-Integrated-with-TradingView-Webhook-Alerts

Python based Trading Bot that uses TradingView.com webhook JSON alerts to place orders(buy/sell/close/manage positions/TP/SL/TS etc.) on Bybit.com.

BybitTelegramBot

The most comprehensive Bybit Telegram Trading Bot(https://t.me/cryptto_ops_bot) in the market for spot trading. Will place orders via TradingView as well as make Manual Trades. For setup ping me @mutemia on telegram or whatsapp: +254728141235

crypto-exchanges-gateway

Your gateway to the world of crypto !

Crypto-Trading-Exchange-

This is a Cryptocurrency Trading Exchange Like Binance, Huobi, Bybit, Bitmex, Bittrex, Phemex etc. That allows you to build your own Centralised Trading Exchange. I have forked it from Jammy928 accessible here: https://github.com/jammy928/CoinExchange_CryptoExchange_Java . I realised Jammy doesn't respond on issues on his repo, and have taken up this mandate to setup the Exchange for anyone who needs it. I can also dpo upgrades as per user requirements, Build iOS and Android Apps of the Exchange, Build Bots like: https://bitsgap.com on top of this for any trading Exchange.

freqtrade-modded-crypto-trading-bot

Freqtrade is an open-source cryptocurrency trading bot written in Python that supports major exchanges. It includes features like backtesting, money management, and machine learning-based strategy optimization.

generative-ai-for-beginners

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

Whatsapp-Business-Bot-with-MPESA-Integration-

A WhatsApp Chat chat bot that can pay bills via MPESA API and manage chats via Twillio API. Can be expanded to make online sales/money transfers/bill payments/group contributions/etc. via WhatsApp and make MPESA payments

Mtemi/Binance-Futures-and-Crypto-Profiles-Algorithm-

A web-based solution that helps a user to manage and optimize their portfolio of cryptocurrencies according to certain criteria. You set how the distribution within the portfolio should change according to how the price of bitcoin changes. This way you can know how much you hold and in what positions; of crypto in various platforms; just on one platform. The algorithm helps you adjust various positions of crypto held in several platforms based on how Bitcoin varies thus advising you whether to buy or sale.

Mtemi/Whatsapp-Business-Bot-with-MPESA-Integration-

A WhatsApp Chat chat bot that can pay bills via MPESA API and manage chats via Twillio API. Can be expanded to make online sales/money transfers/bill payments/group contributions/etc. via WhatsApp and make MPESA payments

Mtemi/autobot

for abc

Mtemi/Bokeh-Market-Depth-Graph

Using Python and Bokeh to live plot a cryptocurrency market depth graph

Mtemi/clownbot

cryptocurrency trader for binance and bittrex

Mtemi/crypto-signal

Automated Crypto Trading & Technical Analysis (TA) Bot for Bittrex, Binance, GDAX, and more! (250+ coins)

Mtemi/etherwallet

Mtemi/fawkes

Fawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes

Mtemi/flask-celery-periodic-task

A simple Flask app to demonstrate Celery periodic task.

Mtemi/flask-react-spa

A production-ready boilerplate built with Python 3, Flask and ES6 React/Redux

Mtemi/gekko

A bitcoin trading bot written in node - https://gekko.wizb.it/

Mtemi/java-dialogflow

Mtemi/phemex

Phemex API

Mtemi/phemex-python-api

Phemex Market Data & Trading API in Python

Mtemi/python-websocket

A Python WebSocket server

Mtemi/Recommendation-systems

Recommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems

Mtemi/Telegram-automatic-message

A python script using the telethon library to simply send messages to a bot every 30 seconds

Mtemi/texttospeech

Google's Speech Synthesis, Text to speech conversion powered by machine learning

Mtemi/WhatsFood

WhatsApp Chatbot for easy group food ordering in your office

Mtemi/wlox

Fully functional multi-currency Bitcoin exchange, adaptable to other cryptocurrencies.