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COMMON MACHINE LEARNING LIBRARIES www.greatlearningminds.com
SCIKIT-LEARN: IDEAL FOR CLASSICAL MACHINE LEARNING ALGORITHMS, IT PROVIDES SIMPLE AND EFFICIENT TOOLS FOR DATA ANALYSIS AND MODELING. TENSORFLOW: DEVELOPED BY GOOGLE, TENSORFLOW IS AN OPEN-SOURCE LIBRARY USED FOR NUMERICAL COMPUTATION AND BUILDING DEEP LEARNING MODELS. PYTORCH: POPULAR FOR ITS DYNAMIC COMPUTATION GRAPH, PYTORCH IS EXTENSIVELY USED FOR DEEP LEARNING AND NEURAL NETWORK RESEARCH. KERAS: BUILT ON TOP OF TENSORFLOW, KERAS IS A HIGH-LEVEL NEURAL NETWORKS API, SIMPLIFYING THE PROCESS OF BUILDING AND TRAINING DEEP LEARNING MODELS. NUMPY: WHILE NOT EXCLUSIVELY A MACHINE LEARNING LIBRARY, NUMPY IS FUNDAMENTAL FOR NUMERICAL COMPUTING AND IS EXTENSIVELY USED IN ML WORKFLOWS. PANDAS: IT PROVIDES HIGH-PERFORMANCE, EASY-TO-USE DATA STRUCTURES AND DATA ANALYSIS TOOLS, MAKING IT VALUABLE FOR DATA MANIPULATION AND CLEANING. www.greatlearningminds.com
MATPLOTLIB: A 2D PLOTTING LIBRARY FOR CREATING STATIC, ANIMATED, AND INTERACTIVE VISUALIZATIONS IN PYTHON. SEABORN: BUILT ON TOP OF MATPLOTLIB, SEABORN PROVIDES A HIGH-LEVEL INTERFACE FOR DRAWING ATTRACTIVE AND INFORMATIVE STATISTICAL GRAPHICS. NLTK (NATURAL LANGUAGE TOOLKIT): WIDELY USED FOR WORKING WITH HUMAN LANGUAGE DATA AND IMPLEMENTING ALGORITHMS FOR TEXT CLASSIFICATION, TOKENIZATION, AND MORE. SCIPY: A LIBRARY FOR MATHEMATICS, SCIENCE, AND ENGINEERING, IT COMPLEMENTS NUMPY AND PROVIDES ADDITIONAL FUNCTIONALITY. XGBOOST: AN OPTIMIZED DISTRIBUTED GRADIENT BOOSTING LIBRARY DESIGNED FOR SPEED AND PERFORMANCE. LIGHTGBM: A GRADIENT BOOSTING FRAMEWORK DEVELOPED BY MICROSOFT THAT IS EFFICIENT AND SCALABLE. www.greatlearningminds.com
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