Hey there, tonydev here! If you're reading this, you're probably as excited about AI and open source as I am. As an AI Tool Guru and enthusiast, I'm always on the lookout for cool projects to contribute to and learn from. And guess what? I've found some gems that I think you'll love.
So, whether you're a seasoned developer or a newbie looking to dip your toes in the world of AI, this list is for you. Let's dive in!
Llama 2 is the next generation of Meta's open source large language model. It's free for research and commercial use, making it a great project to contribute to.
→ Large community support from both Meta and Microsoft.
→ Good for those interested in large language models and natural language processing.
→ Requires knowledge of Python and machine learning concepts.
→ Opportunity to contribute to a project that's at the forefront of AI research.
DeepChem aims to provide a high-quality open-source toolchain that democratizes the use of deep learning in drug discovery, materials science, quantum chemistry, and biology.
→ Ideal for those interested in the intersection of AI and chemistry/biology.
→ Active community and well-maintained project.
→ Good understanding of deep learning, chemistry/biology, and Python is required.
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark.
→ Backed by Facebook AI Research, ensuring a large and active community.
→ Ideal for those interested in object detection algorithms and computer vision.
→ Requires knowledge of Python, PyTorch, and understanding of deep learning concepts.
→ Opportunity to contribute to a project that's pushing the boundaries of computer vision.
Theano is a Python library that lets you define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).
→ Supported by a large community of machine learning enthusiasts.
→ Good for those interested in mathematical computations and multi-dimensional arrays.
→ Requires knowledge of Python and NumPy.
→ A chance to contribute to a project that's widely used in the machine learning community.
Apache MXNet is an open-source deep learning software framework, used to train, and deploy deep neural networks. It is known for its capabilities in handling multiple data formats.
→ Backed by Apache, ensuring a large community support.
→ Ideal for those interested in deep learning and handling multiple data formats.
→ Requires knowledge of Python and deep learning concepts.
→ Opportunity to contribute to a project that's used by many in the AI industry.
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.
→ Large community of developers interested in computer vision and machine learning.
→ Good for those interested in real-time computer vision applications.
→ Requires knowledge of C++, Python, and understanding of computer vision concepts.
→ A chance to contribute to a project that's widely used in the computer vision industry.
Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, answer extraction, summarization, translation, text generation, etc in 100+ languages. Its aim is to make cutting-edge NLP easier to use for everyone.
→ Supported by HuggingFace, a leading company in natural language processing.
→ Ideal for those interested in NLP tasks such as classification, information extraction, summarization, etc.
→ Requires knowledge of Python, PyTorch or TensorFlow, and understanding of NLP concepts.
→ Opportunity to contribute to a project that's making NLP more accessible to everyone.
So, whether you're a seasoned developer or a newbie looking to dip your toes in the world of AI, this list is for you. Let's dive in!
1. Llama 2 by Meta and Microsoft
Llama 2 is the next generation of Meta's open source large language model. It's free for research and commercial use, making it a great project to contribute to.
→ Large community support from both Meta and Microsoft.
→ Good for those interested in large language models and natural language processing.
→ Requires knowledge of Python and machine learning concepts.
→ Opportunity to contribute to a project that's at the forefront of AI research.
2. DeepChem
DeepChem aims to provide a high-quality open-source toolchain that democratizes the use of deep learning in drug discovery, materials science, quantum chemistry, and biology.
→ Ideal for those interested in the intersection of AI and chemistry/biology.
→ Active community and well-maintained project.
→ Good understanding of deep learning, chemistry/biology, and Python is required.
3. Detectron2
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark.
→ Backed by Facebook AI Research, ensuring a large and active community.
→ Ideal for those interested in object detection algorithms and computer vision.
→ Requires knowledge of Python, PyTorch, and understanding of deep learning concepts.
→ Opportunity to contribute to a project that's pushing the boundaries of computer vision.
4. Theano
Theano is a Python library that lets you define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).
→ Supported by a large community of machine learning enthusiasts.
→ Good for those interested in mathematical computations and multi-dimensional arrays.
→ Requires knowledge of Python and NumPy.
→ A chance to contribute to a project that's widely used in the machine learning community.
5. MXNet
Apache MXNet is an open-source deep learning software framework, used to train, and deploy deep neural networks. It is known for its capabilities in handling multiple data formats.
→ Backed by Apache, ensuring a large community support.
→ Ideal for those interested in deep learning and handling multiple data formats.
→ Requires knowledge of Python and deep learning concepts.
→ Opportunity to contribute to a project that's used by many in the AI industry.
6. OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.
→ Large community of developers interested in computer vision and machine learning.
→ Good for those interested in real-time computer vision applications.
→ Requires knowledge of C++, Python, and understanding of computer vision concepts.
→ A chance to contribute to a project that's widely used in the computer vision industry.
7. HuggingFace Transformers
Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, answer extraction, summarization, translation, text generation, etc in 100+ languages. Its aim is to make cutting-edge NLP easier to use for everyone.
→ Supported by HuggingFace, a leading company in natural language processing.
→ Ideal for those interested in NLP tasks such as classification, information extraction, summarization, etc.
→ Requires knowledge of Python, PyTorch or TensorFlow, and understanding of NLP concepts.
→ Opportunity to contribute to a project that's making NLP more accessible to everyone.
