BTC 3-Minute Direction Predictor

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@mohjib092

Hello, I can build a lightweight BTC prediction system that ingests historical price data, engineers trading features, and trains a fast machine learning model (LightGBM / optional LSTM) to predict short-term “Up/Down” movements. The system will include full backtesting on unseen data, clear accuracy reporting, and a real-time signal bot that sends predictions instantly to Telegram or Discord within seconds. You will receive clean source code (Python), trained model, backtest results, and simple deployment instructions. The focus will be on speed, accuracy validation, and a stable real-time pipeline optimized for 3–4 minute forecasting. Let's Chat

@toriquldev123

Hello Dear! Greetings from Toriqul Global Solutions! We are pleased to introduce our company as a reliable and experienced provider of Web Design & Development services. Founded and led by Engineer Toriqul Islam, a B.Sc. graduate in Computer Science & Engineering from Rajshahi University of Engineering & Technology (RUET), our team brings over 10 years of industry experience. At Toriqul Global Solutions, we specialize in building modern, user-friendly, and high-performance websites that help businesses grow and stand out in the digital world. Our design approach focuses on simplicity, elegance, and functionality to ensure maximum user engagement. Technologies We Use: Custom Websites Development Using ======>Full Stack Development. 1. HTML5 2. CSS3 3. Bootstrap4 4. jQuery 5. JavaScript 6. Angular JS 7. React JS 8. Node JS 9. WordPress 10. PHP 11. Ruby on Rails 12. MYSQL 13. Laravel 14. .Net 15. CodeIgniter 16. React Native 17. SQL / MySQL 18. Mobile app development 19. Python 20. MongoDB What you'll get? • Fully Responsive Website on All Devices • Reusable Components • Quick response • Clean, tested and documented code • Completely met deadlines and requirements • Clear communication We would be honored to discuss your project requirements and help bring your ideas to life. Thank you for your time and consideration. Warm Regards, Toriqul Global Solutions

@devanshkhandekar

Hi,I’m a seasoned Applied ML Engineer(6+ yoe) with experience of building time-series ML,forecasting,backtesting pipelines,& production alerts/bots Relevant Experience: >>PHM & RUL Modeling:Developed vibration-log pipelines using rolling statistics,residual health indicators & survival forecasting with time-window validation >>Time-Series Signal Pipelines:Built historical ingestion & feature extraction systems with temporal train/test splits & backtesting reporting >>Real-Time Deployment:Engineered low-latency FastAPI/Flask services & bots for pushing inference results to downstream systems Proposed Approach: >>Data Pipeline:Ingest historical OHLCV data via CCXT or CSV to engineer momentum, volatility, and technical indicators (RSI, MACD, EMA) across 1–15 min windows. >>Modeling:Binary classification (Up/Down) based on a 3–4 minute horizon. I will benchmark XGBoost/LightGBM against LSTM/GRU using strict time-based splits to prevent leakage. >>Backtesting:Performance evaluation using accuracy, precision/recall, win/loss streaks, and market-condition analysis. >>Deployment:A Python-based (FastAPI/Cron) inference engine integrated with Telegram/Discord for real-time signal delivery Tech Stack & Deliverables >>Stack:pandas, Scikit-learn, XGBoost, PyTorch, CCXT, and Docker. >>Milestones: 1. Feature engineering & data prep. 2. Baseline model & backtest reporting. 3. Bot/API integration. 4. Final deployment documentation and logging setup.

@nemanjam61

Hello, I have experience with data ingestion and machine learning for predictive analytics and have built systems that leverage real-time data for actionable insights. I can develop a lightweight application that processes historical BTC price data, applies a predictive model achieving over 70% accuracy, and sends "Up" or "Down" messages to Telegram or Discord within the required four-minute timeframe. For implementation, I would use a robust data pipeline with fast data-fetching strategies and optimize the model for rapid inference. Let's discuss!

@Noorulamin331

Hi, I can build your BTC price prediction app targeting 70%+ accuracy for 3-4 minute windows. I will use XGBoost on engineered features (returns, RSI, MACD, volume, volatility) with walk-forward validation to prevent lookahead bias. Backtest on unseen historical data proves accuracy. Inference runs in seconds, then sends "Up/Down" to Telegram or Discord via telethon/discord.py. Deliverables: Python source code, trained model + notebook, backtest report, deployment instructions, and messaging bot. Timeline 2-3 weeks. Looking forward to working with you. Best regards,

@kingxanda

Hey, Thanks for your post. I'v read your description carefully. I have relevant experience I can help. some of my skills are: Smart Contracts, Ethereum, Blockchain, Metamask and React.js Hope you're having a nice day my friend :)

@jay8mac

Lets chat, a free consultation and no obligation. I understand you need a clean, professional, and user-friendly solution for your "BTC 3-Minute Direction Predictor" project. My skills in PHP, Java, JavaScript are a perfect fit for this project. While I am new to freelancer.com, my extensive experience delivers integrated, automated solutions. Regards, Jason McLachlan

@rishi9343

As an astute AI developer with years of experience in not only mobile development but also in backend service development and database optimization, I embody the perfect blend of skills required for your BTC 3-Minute Direction Predictor project. My proficiency in Python and my deep-rooted understanding of Artificial Intelligence and Machine Learning techniques would be instrumental in creating a high-level application that precisely predicts the direction of Bitcoin prices. My approach to feature engineering would be to leverage frameworks like pandas, scikit-learn, PyTorch/TensorFlow to meticulously analyze the historical data. For model architecture, I suggest incorporating LSTM (Long Short Term Memory) or a lightweight transformer due to their excellent sequence prediction capabilities. This meticulous selection ensures an impressive inference time performance without compromising on the desired accuracy level.

@manthank44

Greetings, I understand your need for a lightweight application to predict BTC price movements with at least 70% accuracy within a three to four-minute timeframe. The focus is on leveraging historical data to make informed decisions and push real-time notifications to your preferred messaging channels, ensuring timely actions for maximizing gains. With a strong background in data-driven solutions and predictive analytics, I have successfully developed similar systems that analyze historical trends, utilizing advanced algorithms such as LSTM for time series forecasting and decision-making. My expertise lies in utilizing a combination of libraries like pandas, scikit-learn, and TensorFlow to extract insights and build robust predictive models. My approach involves meticulous feature engineering on historical BTC price data, implementing a predictive model architecture tailored to the cryptocurrency market dynamics. By prioritizing model accuracy and speed, I ensure the back-testing results showcase the efficacy of the prediction system before deploying the solution. I aim to deliver the source code, trained model, back-testing results, and deployment instructions within the estimated timeline for your review and approval. Best regards, Manthan

@jasonp275

Dear Client, How are you? I hope this proposal finds you well. I'M A CERTIFIED & EXPERIENCED EXPERT This is to inform you that I have KEENLY gone through your project description, CLEARLY understood all the project requirements as instructed in your project proposal and this is to let you know that I will perfectly deliver as desired. Being in possession of all stated required skills as this is my field of professional specialization having completed all certifications and developed adequate experience in the respective field, I hereby humbly request you to consider my bid for professional, quality and affordable services that meet all your requirements. I always guarantee timely delivery and unlimited revisions where necessary hence you are assured of utmost satisfaction when working with me. Please send me a message so that we can discuss more and seal the project. WELCOME.

@mairaj001

Hi, I can build this full BTC prediction pipeline in Python historical OHLCV data ingestion, feature engineering covering price momentum, volume indicators, RSI, MACD, and rolling volatility, an LSTM or gradient boosting model trained and validated on unseen candles with a clear backtest report showing measured 70%+ accuracy, fast inference keeping the full pipeline comfortably under the 4-minute window, and automated Up/Down signal dispatch to Telegram and/or Discord immediately after prediction. Approach: LightGBM as primary model for speed and interpretability with LSTM as comparison baseline, pandas and scikit-learn for feature engineering, backtest on 6–12 months of unseen 1-minute Binance candles, telethon or python-telegram-bot for signal dispatch. Milestones: Data pipeline and feature engineering 2 days, model training and backtest report 3 days, signal bot and deployment 2 days. Deliverables: Source code, trained model, training notebook, backtest results, deployment instructions, and signal bot. Quick question: do you want signals on a fixed 3–4 minute schedule around the clock or only during specific trading hours? Best regards, Mairaj Ahmed

@sertev2022

Hi, I have carefully gone through your project's details, I can assure you that the project is feasible because it falls within my area of expertise. I possess the requisite skills and vast Experience to do and high-quality work is 100% guaranteed. I submit my bid to you, and I appreciate your consideration. With Regards.

@danas79

⭐⭐⭐⭐⭐ I can build a lightweight, low-latency BTC direction prediction system with a strong focus on measurable accuracy and reproducibility, leveraging my experience in time-series modeling and real-time ML pipelines. My approach uses high-frequency historical candle data with engineered features such as returns, volatility, RSI, EMA crossovers, order book proxies, and short-term momentum signals, feeding into a hybrid model (optimized LightGBM for speed and interpretability, optionally benchmarked against LSTM/Transformer for comparison). I will implement strict walk-forward backtesting on unseen data to validate ≥70% directional accuracy, with clear metrics and no data leakage. The pipeline will be built in Python using pandas, NumPy, scikit-learn, and PyTorch (if deep learning is used), with fast inference (<1s) and automated signal delivery via Telegram/Discord bots. Deliverables include clean, documented source code, training scripts, saved model artifacts, reproducible backtesting reports, and deployment instructions. I can complete data pipeline + baseline model in 2–3 days, validated backtesting and optimization in 2 days, and messaging integration + final deployment within 1–2 days.

@thaakirh8

I am a perfect fit for your project, understanding the need for a clean, professional, and user-friendly application that seamlessly ingests historical BTC price data, delivers automated predictions with 70%+ accuracy, and integrates instantly with messaging platforms like Telegram or Discord. My expertise includes Python development, time-series analysis, and building lightweight models such as LSTM and gradient boosting. While I am new to freelancer, I have tons of experience and have done other projects off site involving real-time data processing and model deployment. I am happy to give a free consultation. I would love to chat more about your project! Regards, Thaakir Hendricks

@ArasakaSystems

Ross here from Arasaka Systems, I hope this message finds you well. I’ve tackled similar predictive modeling projects involving financial time series that required clean, professional, and integrated solutions with an emphasis on high performing accuracy. Your need for a lightweight app that predicts BTC price direction with 70%+ accuracy and delivers real-time Up/Down signals perfectly aligns with my expertise. I used to operate Arasaka Systems from Cape Town, South Africa, and am now excited about expanding our reach internationally. My skill set includes Python development, advanced feature engineering, LSTM and gradient boosting modeling, and integration with messaging APIs like Telegram and Discord. I prioritize fast inference pipelines and thorough back-testing to ensure reliability. I appreciate you looking over my proposal, it would be a pleasure to be of assistance. Regards, Ross, Arasaka Systems

@prudhviraj3

I understand you need a real-time system that predicts whether BTC price will go up or down in the next 3–4 minutes with ≥70% accuracy validated on unseen data. I will approach this as a short-term signal detection problem, focusing on accuracy, speed, and robustness. I will build a pipeline that ingests high-frequency BTC data (via Binance/CCXT), processes it into consistent intervals, and generates features like short-window returns, momentum, volatility, lag signals, and lightweight indicators (EMA, RSI, Bollinger Bands). Only high-impact features will be retained to reduce noise. For modeling, I will use LightGBM/XGBoost for strong performance and fast inference. The model will be validated using walk-forward testing to avoid leakage, and I will provide a clear backtesting report proving the ≥70% accuracy on unseen data. The final system will include a real-time loop that fetches data, runs predictions within seconds, and sends instant “Up”/“Down” signals to Telegram or Discord. You will receive clean Python code, trained models, backtesting results, and deployment instructions. The solution will be optimized for low latency, reliability, and real-world