Welcome to the official Dataflow Tech Stack documentation. Here, we highlight the tools and technologies that empower our research and development efforts in Data Science and Machine Learning + Hackathons List.

Hackathons List

• DevPost
• LabLab AI
• CodenRock
• Kaggle Competitions
• Raptors.Dev

ML Problem Solving Platforms

• DeepML
• CodeRun
• LeetGPU
• Hackerearth ML

ML Hands-On Learning Platforms

• Google ML Crash Course
• Yandex ML Trainings 1.0 (ML Fundamentals)
• Yandex ML Trainings 2.0 (NLP)
• Yandex ML Handbook
• FreeCodeCamp ML
• Coursera ML Courses by DeepLearning.AI

Programming Languages

• Python: Our primary language for data analysis, machine learning, and backend development.
• JavaScript: Utilized for interactive web development and backend services.
• C++: Used for performance-critical applications and certain machine learning tasks.

Machine Learning Frameworks

• Scikit-learn: For classical machine learning algorithms and data preprocessing.
• TensorFlow: Employed for building and training deep learning models.
• PyTorch: Preferred for its flexibility in deep learning research and development.

Backend Frameworks

• Flask: A lightweight framework for building simple and scalable web applications.
• FastAPI: Utilized for creating high-performance APIs.
• NodeJS: Used for building scalable server-side applications and APIs.

Web Development

• Streamlit: For creating quick and interactive data-driven web applications.
• Gradio: A user-friendly framework for building machine learning demos and interfaces.

DevOps Tools

• Docker: For containerizing applications to ensure consistency across different environments.
• Git: Essential for version control and collaboration on code.
• GitHub: Our platform of choice for hosting and managing code repositories.

Cloud Computing

• Azure: Our preferred cloud service for deploying and scaling applications and services.
• AWS: Utilized for a wide range of cloud computing services and solutions.

AI Tools

• Gemini AI: Used for advanced AI research and applications.
• Perplexity: AI-based search engine for data analysis and research.
• OpenAI GPT-4: Cutting-edge language model for natural language processing tasks.
• Hugging Face Transformers: A library for state-of-the-art natural language processing models.
• Claude AI: AI-powered assistant for data analysis and visualization.
• DeepSeek: AI tool for deep learning research and development.

Conclusion

At Dataflow, we continuously adopt and integrate cutting-edge tools and technologies to stay at the forefront of research and development in Data Science and Machine Learning. This tech stack represents our commitment to delivering innovative solutions and advancing the field.

For more information and updates, please visit our YouTube channel.

Thank you for your interest in Dataflow! We look forward to collaborating and sharing our journey with you.