“…For data analysis, percentage statistics were applied and to test the hypothesis, the T Student statistical test, and as a result, in the gymnastic program, 100% obtained a bad grade in almost all the basic gymnastics exercises before the application of the program. and after application of the program the performance of these gymnastic exercises is performed excellently in more than 50% of the girls. Comparing these results with the evaluation after the application of the DEPREPCEP Program, learning improves significantly. …”

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“…You'll cover popular topics, including intent classification and sentiment analysis, and use them on popular datasets and interpret the classification results.By the end of this book, you'll be able to confidently use spaCy, including its linguistic features, word vectors, and classifiers, to create your own NLP apps.What you will learn* Install spaCy, get started easily, and write your first Python script* Understand core linguistic operations of spaCy* Discover how to combine rule-based components with spaCy statistical models* Become well-versed with named entity and keyword extraction* Build your own ML pipelines using spaCy* Apply all the knowledge you've gained to design a chatbot using spaCyWho this book is forThis book is for data scientists and machine learners who want to excel in NLP as well as NLP developers who want to master spaCy and build applications with it. …”

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“…Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments.By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source.What you will learnUse Python data science packages effectivelyClean and prepare data for data science work, including feature engineering and feature selectionData modeling, including classic statistical models (such as t-tests), and essential machine learning algorithms, such as random forests and boosted modelsEvaluate model performanceCompare and understand different machine learning methodsInteract with Excel spreadsheets through PythonCreate automated data science reports through PythonGet to grips with text analytics techniquesWho this book is forThe book is intended for beginners, including students starting or about to start a data science, analytics, or related program (e.g. …”

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