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MapclassifyClassification schemes for choropleth mapping.
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SimpsonrecognitionDetect and recognize The Simpsons characters using Keras and Faster R-CNN
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Mlj.jlA Julia machine learning framework
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Face Mask DetectionFace masks are crucial in minimizing the propagation of Covid-19, and are highly recommended or even obligatory in many situations. In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert people that do not wear a mask when entering a building.
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Traffic SignsBuilding a CNN based traffic signs classifier.
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Machine Learning With PythonPractice and tutorial-style notebooks covering wide variety of machine learning techniques
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Ner BertBERT-NER (nert-bert) with google bert https://github.com/google-research.
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Food Recipe Cnnfood image to recipe with deep convolutional neural networks.
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Anomaly detectionThis is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.
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Bayesian Neural NetworksPytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
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Practical Machine Learning With PythonMaster the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
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Mlstm FcnMultivariate LSTM Fully Convolutional Networks for Time Series Classification
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RemixautomlR package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.
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PycaretAn open-source, low-code machine learning library in Python
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Tensorflow BookAccompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
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ServenetService Classification based on Service Description
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Machine Learning From ScratchSuccinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.
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Urban Sound ClassificationUrban sound source tagging from an aggregation of four second noisy audio clips via 1D and 2D CNN (Xception)
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pyts-reproA repository to compare the performance between the algorithms implemented in pyts and the performance reported in the literature
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StingrayAnything can happen in the next half hour (including spectral timing made easy)!
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Kaggle CompetitionsThere are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
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TsmoothieA python library for time-series smoothing and outlier detection in a vectorized way.
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Openml RR package to interface with OpenML
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GlassesHigh-quality Neural Networks for Computer Vision 😎
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