Get to grips with building robust XGBoost models using Python and scikit-learn for deploymentKey FeaturesGet up and running with machine learning and understand how to boost models with XGBoost in no timeBuild real-world machine learning pipelines and fine-tune hyperparameters to achieve optimal resultsDiscover tips and tricks and gain innovative insights from XGBoost Kaggle winnersBook DescriptionXGBoost is an industry-proven, open-source software library that provides a gradient boosting framework for scaling billions of data points quickly and efficiently.
Build and backtest your algorithmic trading strategies to gain a true advantage in the marketKey FeaturesGet quality insights from market data, stock analysis, and create your own data visualisationsLearn how to navigate the different features in Python's data analysis librariesStart systematically approaching quantitative research and strategy generation/backtesting in algorithmic tradingBook DescriptionCreating an effective system to automate your trading can help you achieve two of every trader's key goals; saving time and making money.
Key FeaturesDiscover how most programmers use the main Python libraries when performing statistics with PythonUse descriptive statistics and visualizations to answer business and scientific questionsSolve complicated calculus problems, such as arc length and solids of revolution using derivatives and integralsWhat you will learnGet to grips with the fundamental mathematical functions in PythonPerform calculations on tabular datasets using pandasUnderstand the differences between polynomials, rational functions, exponential functions, and trigonometric functionsUse algebra techniques for solving systems of equationsSolve real-world problems with probabilitySolve optimization problems with derivatives and integralsWho this book is forIf you are a Python programmer who wants to develop intelligent solutions that solve challenging business problems, then this book is for you.
Solve real-world statistical problems using the most popular R packages and techniquesKey FeaturesLearn how to apply statistical methods to your everyday research with handy recipesFoster your analytical skills and interpret research across industries and business verticalsPerform t-tests, chi-squared tests, and regression analysis using modern statistical techniquesBook DescriptionR is a popular programming language for developing statistical software.
Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniquesAbout This BookGain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packagesUnderstand how to apply useful data analysis techniques in R for real-world applicationsAn easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysisWho This Book Is ForThis book is for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages.
Over two hundred novel and innovative computer algebra worksheets or "e;recipes"e; will enable readers in engineering, physics, and mathematics to easily and rapidly solve and explore most problems they encounter in their mathematical physics studies.
Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art in PLS-PM research.
Master the concepts and techniques of statistical analysis using JMPPractical Data Analysis with JMP, Third Edition, highlights the powerful interactive and visual approach of JMP to introduce readers to statistical thinking and data analysis.
Master the concepts and techniques of statistical analysis using JMPPractical Data Analysis with JMP, Third Edition, highlights the powerful interactive and visual approach of JMP to introduce readers to statistical thinking and data analysis.
Geographic information systems (GIS) is a rapidly advancing field that has become thoroughly integrated into our society and inseparable from our daily lives.
Explore biostatistics using JMP(R) in this refreshing introductionPresented in an easy-to-understand way, Introduction to Biostatistics with JMP introduces undergraduate students in the biological sciences to the most commonly used (and misused) statistical methods that they will need to analyze their experimental data using JMP.
Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data.
Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data.
