![]() ![]() Gensim is designed to handle large text collections using data streaming and incremental online algorithms, which differentiates it from most other machine learning software packages that target only in-memory processing. Gensim is implemented in Python and Cython. Gensim is an open-source library for unsupervised topic modeling and natural language processing, using modern statistical machine learning. In Theano, computations are expressed using a NumPy-esque syntax and compiled to run efficiently on either CPU or GPU architectures. Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones. Chollet also is the author of the XCeption deep neural network model. It was developed as part of the research effort of project ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System), and its primary author and maintainer is François Chollet, a Google engineer. Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML. Keras is an open-source neural-network library written in Python. It is accompanied by a book that explains the underlying concepts behind the language processing tasks supported by the toolkit, plus a cookbook. NLTK includes graphical demonstrations and sample data. It was developed by Steven Bird and Edward Loper in the Department of Computer and Information Science at the University of Pennsylvania. The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It is used for both research and production at Google. It is a symbolic math library, and is also used for machine learning applications such as neural networks. TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Scikit-learn (formerly scikits.learn) is a free software machine learning library for the Python programming language. An extensive list of descriptive statistics, statistical tests, plotting functions, and result statistics are available for different types of data and each estimator. Statsmodels is a Python package that allows users to explore data, estimate statistical models, and perform statistical tests. The name is derived from the term “panel data”, an econometrics term for data sets that include observations over multiple time periods for the same individuals. It is free software released under the three-clause BSD license. In particular, it offers data structures and operations for manipulating numerical tables and time series. Pandas is a software library written for the Python programming language for data manipulation and analysis. ![]() SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering. SciPy is a free and open-source Python library used for scientific computing and technical computing. NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Python gained a lot of traction in the world of data science and now has a host on fantastic libraries that support your requirements: Library Its language constructs and object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects. ![]() Created by Guido van Rossum and first released in 1991, Python’s design philosophy emphasizes code readability with its notable use of significant whitespace. ![]() Python is an interpreted, high-level, general-purpose programming language. ![]()
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