If you are taking an Artificial intelligence training and want to know about the latest impactful AI projects, then Github is the right place to look for. Developers need to keep themselves updated with the latest technology and Github is the platform where you can get all the information on AI projects. So, if you are familiar with the basics of artificial intelligence and machine learning, here are some AI projects in Github to look for.
TensorFlow
TensorFlow is the most popular open-source machine learning framework which has an array of features to talk about. It has a wide collection of libraries and tools aided with community resources that allow developers with an Artificial intelligence certification to build ML applications without much effort. It has high-end ML frameworks and APIs such as Keras which makes multiple tasks like debugging and model iterating easy. TensorFlow can be used to train and deploy models through multiple platforms and languages, has over 1,46,000 stars and is a product of Google Brain team.
Pytorch vs Tensorflow vs Keras
Scikit-learn
Built on SciPy, scikit-learn is a Python module for ML. For Python and Artificial Intelligence developers, it is an excellent tool to work on. With the help of this platform, you can use Python for machine learning. It is also built on Matplotlib and NumPy and can be reused on multiple contexts. This is one of the top ML projects in Github that can be used for various AI applications. It also allows the usage of prominent algorithms such as K-means clustering and random forest and has over 41,000 stars.
Handson-ml
Apart from a good Artificial Intelligence training course, this project is a good place if you want to read about the basic of deep learning and machine learning in Python through its Jupyter notebooks. Jupyter notebooks are a product of jupyter.org. These digital books come with interactive code and visuals making them a great mode of learning for developers. This project primarily provides problems related to TensorFlow and scikit-learn.
Qix
With more than 13,000 stars, it one of the top-rated AI projects in Github. It hosts a collection of resources that are used by professionals taking Artificial intelligence course to learn more about machine learning and artificial intelligence. Though most of its content in in Chinese, still you can find translated versions of Chinese papers on various topics related to ML on this project, as well.
PredictionIO
PredictionIO is a product of Apache known to create predictive engines for ML projects. It is a open source ML framework which produces predictive results on deploying, event collection, evaluation and querying. Based on other prominent open source codes, it evaluates multiple engine versions, enhance the existing ML modelling, responds to real time queries and simplifies the management of data infrastructure. It has more than 12,400 stars on Github page and can be installed as a part of the machine learning stack.
LightGBM
Based on decision tree algorithms, LightGBM is a high-performance framework used for gradient boosting. You can use it for classification, ranking and various ML applications. It is a product of Microsoft and gives several advantages for a developer to work on. Handling large-scale data, supporting GPU and parallel learning, high accuracy, low memory consumption, and high efficiency and speed are its advantages making it a great choice for developers. Developers using this project has claimed that LightGBM is capable of beating other boosting frameworks in terms of accuracy and efficiency. Any issues encountered while using LightGBM can be discussed over its existing communities on Slack and other platforms.
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Conclusion
Github is a place where you can look for various Artificial Intelligence and ML projects serving different purposes. The above are among the top projects that an AI developer would require during his journey of AI and ML learning and applications.
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