mdhasanai,Md Hasan,mdhasanai,github

Hello World!

About Me

🎓 I'm currently pursuing my MSc in Artificial Intelligence.

🔭 I'm passionate about Deep Learning (DL) and Large Language Models (LLMs), and I'm actively working on creating innovative AI products leveraging these technologies.

🌱 I'm on a continuous learning journey, currently focusing on mastering MLOps to streamline the deployment and management of machine learning models.

👯 I'm always open to collaboration on exciting Deep Learning projects, especially those involving Image/Video-based detection, recognition, segmentation, and Natural Language Processing (NLP).

💼 In addition to my academic pursuits, I also enjoy discussing AI ethics, the societal impact of AI, and the future of technology.

⚡ Fun fact 1: Fun fact: I once tried to teach a neural network to make me coffee, but it just kept brewing endless cups of chaos. ☕😄

📫 You can reach me at: [email protected] Feel free to explore my GitHub repositories to see some of my recent projects and contributions. Let's connect and create some AI magic together! 🚀

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Md Hasan's Projects

mmdetection

Open MMLab Detection Toolbox and Benchmark

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

pytorch-frn

Filter Response Normalization Layer in PyTorch

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

TNN: developed by Tencent Youtu Lab and Guangying Lab, a lightweight and high-performance deep learning framework for mobile inference. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework. TNN：由腾讯优图实验室和光影实验室协同打造，移动端高性能、轻量级推理框架，同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。TNN框架在原有Rapidnet、ncnn框架的基础上进一步加强了移动端设备的支持以及性能优化，同时也借鉴了业界主流开源框架高性能和良好拓展性的优点。目前TNN已经在手Q、微视、P图等应用中落地，欢迎大家参与协同共建，促进TNN推理框架进一步完善。