Pattern recognition projects uses machine learning to recognize patterns such as images, text, and speech. It can help to predict patterns for example in Forex trading. In this article, we look at the top 20 pattern recognition projects you can work on.
This is a wrapper built with Python for TA-Lib. TA-Lib is a market analysis tool that is primarily used by developers who create trading software. It uses Numpy and Cython to seamlessly wrap TA-Lib.
Do you want to learn Tensorflow? Well, why not use this pattern recognition project. It comes with comprehensive tutorials ensuring you are well-equipped with the basics. You’ll also love how simple the code is.
Papers Literature MI DI RI Ai
If you want crucial information on machine learning, artificial intelligence, deep learning, and game theory, this project got you sorted. It has some of the most sort after papers in these fields.
This is yet another repository with rich notes on machine learning and pattern recognition. You’ll also get pattern recognition replicas from this repo. It is free to use and Christopher Bishop updates it regularly.
Deep Learning Drizzle
If you don’t like reading notes, you can opt for past lectures. And this is what deep learning drizzle affords you. You get to learn more about Computer Vision, Machine Learning, and more.
This project has datasets and code for Tsetlin Machine so you can use it seamlessly. Tsetlin Machine is used to solve complex pattern recognition challenges. It uses propositional formulas to do this.
If you want to analyze anomalies and patterns from Grafana, this repository got you sorted. It uses pattern recognition to identify anomalies through Hastic implementation. It is free to use and contribute.
Not So Random
This interesting script will try to guess your next input. It uses pattern recognition to come up with a randomized pattern to guess the next input.
This pyramidal Convolution gives you a different Convolutional Neural Networks angle. It comes with an ImageNet trained model for better results. If you want to improve its accuracy, you can use complex training methods.
Hastic Grafana App
This is yet another repository that enables you to label anomalies and patterns is Grafana. All you need is the hastic-server and Grafana 5.4.0 or higher. Should you want any help, you can contact the CorpGlory team.
Iresnet is based on the “Improved Residual Networks for Image and Video Recognition” paper. The PyTorch implementation is trained on ImageNet. It enables the improvement of the baseline (ResNet) recognition performance. The best part, it does this cost-effectively.
This project is based on the research paper “learning Discriminative Features with Multiple Granularities for Person RE-Identification. While offering robust results, it is still undergoing regular updates. Its code is however PyTorch 0.4 and Python 2.7 tested.
If you want an extra fast Computer Vision library, Compv is the perfect choice for you. the open-source library boasts to be 50 times faster than conventional OpenCV. With it, you get smart multithreading and memory access.
This is a Scala-based library. It is used to design and train Artificial Neural Networks. It allows you to do this simply and gradually. And thanks to the easy-to-follow instructions, you’ll find the process a walk in the park.
This software works on large data sets. With it to extra patterns from such data will be a walk in the park. It uses n-gram, skipgram, and flexgram categories to extract statistics from the patterns.
Logisland is built with Spark and Kafka providing much-needed analytics. It can also work with Kafka Streams and MQTT. It is intended for the complex processing of events thanks to an array of data sources, processors, and sinks.
This predictive power assessment software works with neuroimaging features to offer a straightforward and comprehensive assessment. It compares many features, is compatible with lots of input formats, and plugs into outputs of popular software.
Cogalg is a Computer Vision implementation software.
Forex And Stock Python Pattern Recognizer
If you want to automate the recognition of patterns in stock or Forex, this pattern recognizer is your perfect bet. You can fork or clone and customize or improve on it.
Computer Vision Notebooks
Finally, we have this collection of Python and Computer Vision notebooks.
Click here for more details.
We hope you can use any of the top 20 Pattern recognition projects on this list to improve your skills. You can contribute to some while others allow you to fork and create unique projects.