From f0132a5caf784f37c640f326d8ab0f8f9b241a48 Mon Sep 17 00:00:00 2001 From: Hemang Joshi Date: Fri, 20 Sep 2024 06:41:17 +0530 Subject: [PATCH] Update README.md --- README.md | 175 +++++++++++++++++++++++------------------------------- 1 file changed, 74 insertions(+), 101 deletions(-) diff --git a/README.md b/README.md index 87125e7..d4347ae 100644 --- a/README.md +++ b/README.md @@ -1,133 +1,106 @@ -Please adda a ⭐ +# TrendMaster: Advanced Stock Price Prediction using Transformer Deep Learning -# TrendMaster: Stock Price Prediction using Transformer Deep Learning Architecture -TrendMaster leverages advanced Transformer deep learning architecture to provide highly accurate stock price predictions, enabling informed investment decisions. +[![Python Version](https://img.shields.io/badge/python-3.7%2B-blue)](https://www.python.org/downloads/) +[![License](https://img.shields.io/badge/license-MIT-green)](https://opensource.org/licenses/MIT) +[![GitHub Stars](https://img.shields.io/github/stars/hemangjoshi37a/TrendMaster?style=social)](https://github.com/hemangjoshi37a/TrendMaster/stargazers) -Utilizing a wealth of data and sophisticated algorithms, TrendMaster stands out as a top-tier tool for financial forecasting. +TrendMaster leverages cutting-edge Transformer deep learning architecture to deliver highly accurate stock price predictions, empowering you to make informed investment decisions. -![Result](https://user-images.githubusercontent.com/12392345/125791380-341cecb7-a605-4147-9310-e5055f30b220.gif) +![TrendMaster Demo](https://user-images.githubusercontent.com/12392345/125791380-341cecb7-a605-4147-9310-e5055f30b220.gif) -## Installation -To get started with TrendMaster, run the following installation command: +## 🚀 Features + +- Advanced Transformer-based prediction model +- High accuracy with mean average error of just a few percentage points +- Real-time data visualization +- User-friendly interface +- Customizable model parameters +- Support for multiple stock symbols + +## 📊 Why TrendMaster? + +TrendMaster stands out as a top-tier tool for financial forecasting by: + +- Utilizing a wealth of historical stock data +- Employing sophisticated deep learning algorithms +- Identifying patterns and trends beyond human perception +- Providing actionable insights for smarter investment strategies + +## 🛠️ Installation + +Get started with TrendMaster in just one command: ```bash pip install TrendMaster ``` -## Usage -Here's how to integrate TrendMaster into your Python projects: +## 📈 Quick Start +Here's how to integrate TrendMaster into your Python projects: ```python from trendmaster import TrendMaster -#Initialize the TrendMaster object + +# Initialize TrendMaster test_symbol = 'SBIN' tm = TrendMaster(symbol_name_stk=test_symbol) -#Load your data + +# Load data data = tm.load_data(symbol=test_symbol) -#Train the model + +# Train the model tm.train(test_symbol, transformer_params={'epochs': 1}) -#Perform inference -predictions = tm.inferencer.predict_future(val_data=data,future_steps=100,symbol=test_symbol) + +# Perform inference +predictions = tm.inferencer.predict_future(val_data=data, future_steps=100, symbol=test_symbol) print(predictions) ``` -## Star History - - - - - - Star History Chart - - +## 📊 Sample Results -Our Transformer-based prediction model is trained on a large dataset of historical stock prices, giving it the ability to identify patterns and trends that would be impossible for a human to discern. The model's predictions are also highly accurate, with a mean average error of just a few percentage points. +Our Transformer-based prediction model demonstrates impressive accuracy: ![Transformer-Future200](https://user-images.githubusercontent.com/12392345/125791397-a344831b-b28c-4660-b295-924cb7123872.png) -In addition to stock price prediction, TrendMaster also offers a range of other features, such as real-time data visualization and a user-friendly interface. With TrendMaster, you'll have all the information you need to make smart investment decisions. +## 🖥️ User Interface -![Screenshot from 2021-07-15 18-26-49](https://user-images.githubusercontent.com/12392345/125791827-a4597af0-1292-42d0-9eb1-118d7ef64cbc.png) +TrendMaster comes with a sleek, user-friendly interface for easy data visualization and analysis: -So why wait? Try TrendMaster today and see the difference for yourself! +![TrendMaster UI](https://user-images.githubusercontent.com/12392345/125791827-a4597af0-1292-42d0-9eb1-118d7ef64cbc.png) +## 📘 Documentation -## 📫 How to reach me -[](https://hjlabs.in/)   -[](https://wa.me/917016525813)   -[](https://t.me/hjlabs)   -[](mailto:hemangjoshi37a@gmail.com)   -[](https://www.linkedin.com/in/hemang-joshi-046746aa)   -[](https://www.facebook.com/hemangjoshi37)   -[](https://twitter.com/HemangJ81509525)   -[](https://www.tumblr.com/blog/hemangjoshi37a-blog)   -[](https://stackoverflow.com/users/8090050/hemang-joshi)   -[](https://www.instagram.com/hemangjoshi37)   -[](https://in.pinterest.com/hemangjoshi37a)   -[](http://hemangjoshi.blogspot.com)   -[](https://gitlab.com/hemangjoshi37a)   +For detailed documentation, including API reference and advanced usage, please visit our [Wiki](https://github.com/hemangjoshi37a/TrendMaster/wiki). -## Checkout Cool GitHub Other Repositories: +## 🤝 Contributing + +We welcome contributions! Please see our [Contributing Guidelines](CONTRIBUTING.md) for more details. + +## 📝 License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. + +## 🌟 Show Your Support + +If you find TrendMaster helpful, please consider giving it a star on GitHub. It helps others discover the project and motivates us to keep improving! + +[![GitHub Star History](https://api.star-history.com/svg?repos=hemangjoshi37a/TrendMaster&type=Date)](https://star-history.com/#hemangjoshi37a/TrendMaster&Date) + +## 📫 Contact + +For questions, suggestions, or collaboration opportunities, please reach out: + +- Website: [hjlabs.in](https://hjlabs.in/) +- Email: [hemangjoshi37a@gmail.com](mailto:hemangjoshi37a@gmail.com) +- LinkedIn: [Hemang Joshi](https://www.linkedin.com/in/hemang-joshi-046746aa) + +## 🔗 More from HJ Labs + +Check out our other exciting projects: - [pyPortMan](https://github.com/hemangjoshi37a/pyPortMan) -- [transformers_stock_prediction](https://github.com/hemangjoshi37a/transformers_stock_prediction) -- [TrendMaster](https://github.com/hemangjoshi37a/TrendMaster) -- [hjAlgos_notebooks](https://github.com/hemangjoshi37a/hjAlgos_notebooks) - [AutoCut](https://github.com/hemangjoshi37a/AutoCut) -- [My_Projects](https://github.com/hemangjoshi37a/My_Projects) -- [Cool Arduino and ESP8266 or NodeMCU Projects](https://github.com/hemangjoshi37a/my_Arduino) -- [Telegram Trade Msg Backtest ML](https://github.com/hemangjoshi37a/TelegramTradeMsgBacktestML) - -## Checkout Our Other Products: -- [WiFi IoT LED Matrix Display](https://hjlabs.in/product/wifi-iot-led-display) -- [SWiBoard WiFi Switch Board IoT Device](https://hjlabs.in/product/swiboard-wifi-switch-board-iot-device) -- [Electric Bicycle](https://hjlabs.in/product/electric-bicycle) -- [Product 3D Design Service with Solidworks](https://hjlabs.in/product/product-3d-design-with-solidworks/) -- [AutoCut : Automatic Wire Cutter Machine](https://hjlabs.in/product/automatic-wire-cutter-machine/) -- [Custom AlgoTrading Software Coding Services](https://hjlabs.in/product/custom-algotrading-software-for-zerodha-and-angel-w-source-code//) -- [SWiBoard :Tasmota MQTT Control](https://play.google.com/store/apps/details?id=in.hjlabs.swiboard) -- [Custom Token Classification or Named Entity Recognition (NER) model as in Natural Language Processing (NLP) Machine Learning](https://hjlabs.in/product/custom-token-classification-or-named-entity-recognition-ner-model-as-in-natural-language-processing-nlp-machine-learning/) - -## Some Cool Arduino and ESP8266 (or NodeMCU) IoT projects: -- [IoT_LED_over_ESP8266_NodeMCU : Turn LED on and off using web server hosted on a nodemcu or esp8266](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_LED_over_ESP8266_NodeMCU) -- [ESP8266_NodeMCU_BasicOTA : Simple OTA (Over The Air) upload code from Arduino IDE using WiFi to NodeMCU or ESP8266](https://github.com/hemangjoshi37a/my_Arduino/tree/master/ESP8266_NodeMCU_BasicOTA) -- [IoT_CSV_SD : Read analog value of Voltage and Current and write it to SD Card in CSV format for Arduino, ESP8266, NodeMCU etc](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_CSV_SD) -- [Honeywell_I2C_Datalogger : Log data in A SD Card from a Honeywell I2C HIH8000 or HIH6000 series sensor having external I2C RTC clock](https://github.com/hemangjoshi37a/my_Arduino/tree/master/Honeywell_I2C_Datalogger) -- [IoT_Load_Cell_using_ESP8266_NodeMC : Read ADC value from High Precision 12bit ADS1015 ADC Sensor and Display on SSD1306 SPI Display as progress bar for Arduino or ESP8266 or NodeMCU](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_Load_Cell_using_ESP8266_NodeMC) -- [IoT_SSD1306_ESP8266_NodeMCU : Read from High Precision 12bit ADC seonsor ADS1015 and display to SSD1306 SPI as progress bar in ESP8266 or NodeMCU or Arduino](https://github.com/hemangjoshi37a/my_Arduino/tree/master/IoT_SSD1306_ESP8266_NodeMCU) - -## Our HuggingFace Models : -- [hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086 : Stock tip message NER(Named Entity Recognition or Token Classification) using HUggingFace-AutoTrain and LabelStudio and Ratnakar Securities Pvt. Ltd.](https://huggingface.co/hemangjoshi37a/autotrain-ratnakar_1000_sample_curated-1474454086) - -## Our HuggingFace Datasets : -- [hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated : Stock tip message NER(Named Entity Recognition or Token Classification) using HUggingFace-AutoTrain and LabelStudio and Ratnakar Securities Pvt. Ltd.](https://huggingface.co/datasets/hemangjoshi37a/autotrain-data-ratnakar_1000_sample_curated) - -## Awesome Youtube Videos : -- [❤️ હદય અને હદયના ધબકારા 💙 दिल और दिल की धड़कन 💖 Heart and beating of heart by Priyanka madam. 💕](https://www.youtube.com/watch?v=9v3MK6oTOeA) -- [🩸 રુધિર વહીનીઓ અને એના કર્યો. 🩸 Blood Vessels And Working of Blood Vessels 🩸 By Priyankama'am](https://www.youtube.com/watch?v=T7mMcEYNKyQ) -- [🩸 મનુષ્યમાં પરિવહન તંત્ર 🩸 परिसंचरण तंत्र 🩸 Blood Circulation System in Humans🩸 By Priyanka madam](https://www.youtube.com/watch?v=vxa6o_wrWnY) -- [AutoCut V2 - The World's Most Powerful Arduino Automatic Wire Cutting Machine](https://www.youtube.com/watch?v=oGr0mWmNhKY) -- [SWiBoard - A Killer Gadget to Boost Your Boring Switchboard](https://www.youtube.com/watch?v=ftza6WM4LiE) -- [🧪 મનુષ્યમાં ઉત્સર્જન-તંત્ર 🦠 मानव उत्सर्जन तंत्र ⚗️ excretory system 🩺](https://www.youtube.com/watch?v=UUGI-CFKsWI) -- [🌳વનસ્પતિમાં પાણી અને ખનીજ તત્વોનું વહન 🌲](https://youtu.be/1da9p6iYlr4) -- [🌲 વનસ્પતિમાં બાષ્પોત્સર્જન 🌳 पेड़ में वाष्पोत्सर्जन 🎄Transpiration in Trees](https://youtu.be/I9Sirc42Ktg) -- [🫁 સજીવોમાં શ્વસન 🧬 जीवों में श्वास 🫀 Breathing in organisms 👩🏻‍🔬](https://youtu.be/sIMl4t2OFmY) -- [🫁 શ્વસનની પ્રક્રિયા 🫀Respiratory System 🦠](https://youtu.be/hua8ZD5Ge1w) -- [🫁 મનુષ્યમાં શ્વાસ અને ઉચ્છશ્વાસ ⚛️ ](https://youtu.be/BI-CYgnkGCw) - -## My Quirky Blog : -- [Hemang Joshi](http://hemangjoshi.blogspot.com/) - -## Awesome Android Apps : -- [SWiBoard :Tasmota MQTT Control](https://play.google.com/store/apps/details?id=in.hjlabs.swiboard) - -## Checkout Cool GitLab Other Repositories: -- [pyPortMan](https://gitlab.com/hemangjoshi37a/pyPortMan) -- [transformers_stock_prediction](https://gitlab.com/hemangjoshi37a/transformers_stock_prediction) -- [TrendMaster](https://gitlab.com/hemangjoshi37a/TrendMaster) -- [hjAlgos_notebooks](https://gitlab.com/hemangjoshi37a/hjAlgos_notebooks) -- [AutoCut](https://gitlab.com/hemangjoshi37a/AutoCut) -- [My_Projects](https://gitlab.com/hemangjoshi37a/My_Projects) -- [Cool Arduino and ESP8266 or NodeMCU Projects](https://gitlab.com/hemangjoshi37a/my_Arduino) -- [Telegram Trade Msg Backtest ML](https://gitlab.com/hemangjoshi37a/TelegramTradeMsgBacktestML) +- [TelegramTradeMsgBacktestML](https://github.com/hemangjoshi37a/TelegramTradeMsgBacktestML) + +--- +Created with ❤️ by [Hemang Joshi](https://github.com/hemangjoshi37a) \ No newline at end of file