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Data science with Python : combine Python with machine learning principles to discover hidden patterns in raw data /

Leverage the power of the Python data science libraries and advanced machine learning techniques to analyse large unstructured datasets and predict the occurrence of a particular future event. Key Features Explore the depths of data science, from data collection through to visualization Learn pandas...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Chopra, Rohan (Autor), England, Aaron (Autor), Alaudeen, Mohamed Noordeen (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2019.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Chopra, Rohan,  |e author. 
245 1 0 |a Data science with Python :  |b combine Python with machine learning principles to discover hidden patterns in raw data /  |c Rohan Chopra, Aaron England and Mohamed Noordeen Alaudeen. 
264 1 |a Birmingham, UK :  |b Packt Publishing,  |c 2019. 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Online resource; title from cover (Safari, viewed November 5, 2019). 
504 |a Includes bibliographical references. 
520 |a Leverage the power of the Python data science libraries and advanced machine learning techniques to analyse large unstructured datasets and predict the occurrence of a particular future event. Key Features Explore the depths of data science, from data collection through to visualization Learn pandas, scikit-learn, and Matplotlib in detail Study various data science algorithms using real-world datasets Book Description Data Science with Python begins by introducing you to data science and teaches you to install the packages you need to create a data science coding environment. You will learn three major techniques in machine learning: unsupervised learning, supervised learning, and reinforcement learning. You will also explore basic classification and regression techniques, such as support vector machines, decision trees, and logistic regression. As you make your way through chapters, you will study the basic functions, data structures, and syntax of the Python language that are used to handle large datasets with ease. You will learn about NumPy and pandas libraries for matrix calculations and data manipulation, study how to use Matplotlib to create highly customizable visualizations, and apply the boosting algorithm XGBoost to make predictions. In the concluding chapters, you will explore convolutional neural networks (CNNs), deep learning algorithms used to predict what is in an image. You will also understand how to feed human sentences to a neural network, make the model process contextual information, and create human language processing systems to predict the outcome. By the end of this book, you will be able to understand and implement any new data science algorithm and have the confidence to experiment with tools or libraries other than those covered in the book. What you will learn Pre-process data to make it ready to use for machine learning Create data visualizations with Matplotlib Use scikit-learn to perform dimension reduction using principal component analysis (PCA) Solve classification and regression problems Get predictions using the XGBoost library Process images and create machine learning models to decode them Process human language for prediction and classification Use TensorBoard to monitor training metrics in real time Find the best hyperparameters for your model with AutoML Who this book is for Data Science with Python is designed for data analysts, data scientists, database engineers, and business analysts who want to m ... 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Python (Computer program language) 
650 0 |a Machine learning. 
650 0 |a Data mining. 
650 0 |a Information visualization. 
650 6 |a Python (Langage de programmation) 
650 6 |a Apprentissage automatique. 
650 6 |a Exploration de données (Informatique) 
650 6 |a Visualisation de l'information. 
650 7 |a Data mining.  |2 fast  |0 (OCoLC)fst00887946 
650 7 |a Information visualization.  |2 fast  |0 (OCoLC)fst00973185 
650 7 |a Machine learning.  |2 fast  |0 (OCoLC)fst01004795 
650 7 |a Python (Computer program language)  |2 fast  |0 (OCoLC)fst01084736 
700 1 |a England, Aaron,  |e author. 
700 1 |a Alaudeen, Mohamed Noordeen,  |e author. 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781838552862/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
994 |a 92  |b IZTAP