Understand data analysis pipelines using machine learning algorithms and techniques with this practical guideKey FeaturesPrepare and clean your data to use it for exploratory analysis, data manipulation, and data wranglingDiscover supervised, unsupervised, probabilistic, and Bayesian machine learning methodsGet to grips with graph processing and sentiment analysisBook DescriptionData analysis enables you to generate value fro...

Key FeaturesBook DescriptionThis book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.What you will learnInstall NumPy, matplotlib, SciPy, and IPython on various operati...

Take tiny steps to enter the big world of data science through this interesting guideKey Features\[\*\] Learn the fundamentals of machine learning and build your own intelligent applications\[\*\] Master the art of building your own machine learning systems with this example-based practical guide\[\*\] Work with important classification and regression algorithms and other machine learning techniquesBook DescriptionData scienc...

Over 140 practical recipes to help you make sense of your data with ease and build production-ready data appsKey FeaturesAnalyze Big Data sets, create attractive visualizations, and manipulate and process various data typesPacked with rich recipes to help you learn and explore amazing algorithms for statistics and machine learningAuthored by Ivan Idris, expert in python programming and proud author of eight highly reviewed booksBo...

Leverage the power of Python to clean, scrape, analyze, and visualize your dataAbout This BookClean, format, and explore your data using the popular Python libraries and get valuable insights from itAnalyze big data sets; create attractive visualizations; manipulate and process various data types using NumPy, SciPy, and matplotlib; and morePacked with easy-to-follow examples to develop advanced computational skills for the analys...

This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.

A step-by-step guide, packed with examples of practical numerical analysis that will give you a comprehensive, but concise overview of NumPy. This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python.

The book is written in beginner's guide style with each aspect of NumPy demonstrated with real world examples and required screenshots. If you are a programmer, scientist, or engineer who has basic Python knowledge and would like to be able to do numerical computations with Python, this book is for you. No prior knowledge of NumPy is required.

If you're a Python developer with basic NumPy skills, the 70+ recipes in this brilliant cookbook will boost your skills in no time. Learn to raise productivity levels and code faster and cleaner with the open source mathematical library.Key FeaturesDo high performance calculations with clean and efficient NumPy codeAnalyze large sets of data with statistical functionsExecute complex linear algebra and mathematical computationsBook...

If you are a Python developer with some experience of working on scientific, mathematical, and statistical applications and want to gain an expert understanding of NumPy programming in relation to science, math, and finance using practical recipes, then this book is for you.

Key FeaturesBook DescriptionPython has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, bio...

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...