20 top-notch educational python machine learning programs for all of you. 1. Scikit-learn Scikit-learn, a Python module based on scipy for machine learning, features a variety of classifications, regression and clustering algorithms including support vector machines, logistic regression, naive Bayesian classifier, random forest, Gradient boosting, clustering algorithm and Dbscan. and also designed Python numerical and scientific libraries Numpy and Scipy 2.pylearn2Pylearn is a Theano-based library program that simplifies machine learning research. 3.NuPICNupic is a machine intelligence platform with the HTM learning algorithm as a tool. The HTM is the precise method of computation of the cortex. The core of HTM is the time-based continuous learning algorithm and the storage and revocation space-time patterns. Nupic is suitable for a wide variety of problems, especially for detecting anomalies and predicting stream data sources. 4. NilearnNilearn is a Python module that is able to quickly statistic and learn neural image data. It uses the Scikit-learn Toolkit in the Python language and some applications for predictive modeling, classification, decoding, and connectivity analysis to perform multivariate statistics. 5.PyBrainPybrain is based on the Python language reinforcement learning, artificial intelligence, neural network library abbreviation. It aims to compare your algorithms by providing flexible, easy-to-use and powerful machine learning algorithms and testing in a variety of pre-defined environments. 6.PatternPattern is a network mining module under the Python language. It provides tools for data mining, natural language processing, network analysis, and machine learning. It supports vector space model, clustering, support vector machine and perceptron and classifies with KNN classification. 7.Fuel fuel provides data for your machine learning model. He has an interface to share data sets such as Mnist, CIFAR-10 (Image dataset), Google's one Billion Words (text). You use him to replace your data in many ways. 8.BobBob is a free tool for signal processing and machine learning. Its toolkit, written in Python and the C + + language, is designed to be more efficient and less development time, consisting of a large number of packages that handle image tools, audio and video processing, machine learning, and pattern recognition. 9.SkdataSkdata is a library of machine learning and statistical data sets. This module provides standard Python language usage for toy problems, popular computer vision and natural language datasets. 10.MILKmilk is a machine learning toolkit under the Python language. It mainly uses supervised taxonomy in many available classifications such as SVMS,K-NN, random forest, decision trees. It also performs feature selection. These classifiers are combined in many ways to form different classification systems such as unsupervised learning, close relationship gold propagation, and K-means clustering supported by milk. 11.IEPYIepy is an open source information extraction tool that focuses on relational extraction. It is focused on users who need to extract information from large datasets and scientists who want to try out new algorithms. 12.QuepyQuepy is a Python framework that makes queries in the database query language by altering natural language problems. He can simply be defined as a different type of problem in natural language and database queries. So you can build your own system that enters your database in natural language without coding. Quepy now provides support for SPARQL and MQL query languages. and plan to extend it to other database query languages. 13.HebelHebel is a library program for deep learning of neural networks in the Python language, using Pycuda for GPU and cuda acceleration. It is the most important type of neural network model tool and can provide some different activation functions for active functions, such as power, Nesterov power, signal loss and stop method. 14.mlxtendIt is a library program that consists of a useful tool and an extension of the daily data Science task. 15.nolearnThis package contains a number of utility modules that can help you complete your machine learning tasks. Many of these modules work with Scikit-learn, and others are usually more useful. 16.RampRamp is a library program that develops a solution for accelerating prototyping in machine learning in the Python language. He is a lightweight pandas-based machine learning pluggable framework, its existing Python language for machine learning and statistical tools such as Scikit-learn, RPY2, etc.) ramp provides a simple declarative syntax exploration function that enables the implementation of algorithms and transformations quickly and efficiently. 17.Feature ForgeThis series of tools creates and tests machine learning features through a Scikit-learn-compatible API. This library program provides a set of tools that will make you very useful in many machine learning programs. When you use the Scikit-learn tool, you will feel a lot of help. (although this can only work if you have different algorithms.) ) 18.REPRep is an environment that is provided in a harmonious, renewable way for directing data movement drivers. it has a uniform classifier wrapper to provide a wide variety of operations, such as TMVA, Sklearn, Xgboost, Uboost and so on. And it can train the classifier in a group in a parallel way. At the same time it also provides an interactive plot. 19.Python Learning Machine Samplessimple software collection built with Amazon's machine learning. 20.python-elmThis is an implementation of an extreme learning machine based on Scikit-learn in the Python language. read through this article do you have a deep understanding of Python, come on!
20 top-notch educational python machine learning programs for all of you.
