Learning Predictive Analytics With Python
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Learning Predictive Analytics with Python
Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Get to grips with the basics of Predictive Analytics with Python Learn how to use the popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Who This Book Is For If you wish to learn how to implement Predictive Analytics algorithms using Python libraries, then this is the book for you. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about Predictive Analytics algorithms, this book will also help you. The book will be beneficial to and can be read by any Data Science enthusiasts. Some familiarity with Python will be useful to get the most out of this book, but it is certainly not a prerequisite. What You Will Learn Understand the statistical and mathematical concepts behind Predictive Analytics algorithms and implement Predictive Analytics algorithms using Python libraries Analyze the result parameters arising from the implementation of Predictive Analytics algorithms Write Python modules/functions from scratch to execute segments or the whole of these algorithms Recognize and mitigate various contingencies and issues related to the implementation of Predictive Analytics algorithms Get to know various methods of importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and numpy Create dummy datasets and simple mathematical simulations using the Python numpy and pandas libraries Understand the best practices while handling datasets in Python and creating predictive models out of them In Detail Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age. This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy. You'll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. Style and approach All the concepts in this book been explained and illustrated using a dataset, and in a step-by-step manner. The Python code snippet to implement a method or concept is followed by the output, such as charts, dataset heads, pictures, and so on. The statistical concepts are explained in detail wherever required.
Python: Advanced Predictive Analytics
Author: Joseph Babcock
language: en
Publisher: Packt Publishing Ltd
Release Date: 2017-12-27
Gain practical insights by exploiting data in your business to build advanced predictive modeling applications About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Who This Book Is For This book is designed for business analysts, BI analysts, data scientists, or junior level data analysts who are ready to move on from a conceptual understanding of advanced analytics and become an expert in designing and building advanced analytics solutions using Python. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about predictive analytics algorithms, this book will also help you. What You Will Learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis In Detail Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling. Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books: 1. Learning Predictive Analytics with Python 2. Mastering Predictive Analytics with Python Style and approach This course aims to create a smooth learning path that will teach you how to effectively perform predictive analytics using Python. Through this comprehensive course, you'll learn the basics of predictive analytics and progress to predictive modeling in the modern world.
Python for Predictive Analytics in Finance
Python for Predictive Analytics in Finance: Anticipate Market Movements Stay Ahead of the Market with Predictive Analytics Using Python! Unlock the power of predictive analytics with Python for Predictive Analytics in Finance: Anticipate Market Movements. This essential guide equips Python programmers, web developers, web application developers, students, and trading enthusiasts with the skills to forecast market trends and make proactive investment decisions, reducing the risks associated with market volatility. Key Features: Comprehensive Insights: Dive deep into predictive analytics using Python. Learn how to leverage powerful tools and techniques to perform financial analytics with Python, giving you a competitive edge in the financial world. Real-World Applications: Explore practical examples and case studies that show how to apply predictive analytics for finance. Understand how to use Python to anticipate market movements and make data-driven investment decisions. Step-by-Step Approach: This book provides clear, step-by-step instructions, making complex concepts accessible to both beginners and experienced programmers. Build your knowledge gradually with detailed explanations and practical exercises on learning predictive analytics with Python. Risk Reduction: Learn how predictive analytics can help you reduce the risks associated with market volatility. Make proactive investment decisions based on data-driven insights rather than speculation. Advanced Techniques: Master advanced techniques in predictive analytics, including machine learning algorithms, statistical modeling, and data visualization. Equip yourself with the skills needed to tackle complex financial data and predict market trends using Python libraries for predictive analytics. Why Choose This Book? Tailored for Your Needs: Whether you're a Python programmer looking to expand your skillset, a web developer interested in financial applications, a student exploring data analysis, or a trading enthusiast seeking to improve your investment strategies, this book is designed with you in mind. Learn how to use Python for financial analysis and become a proficient financial analyst. Written in an engaging and persuasive tone, this book not only teaches you the technical skills but also inspires you to apply them effectively. Transform your approach to financial data with análise financeira com Python and anticipate market movements with confidence. Informed Investment Decisions: By the end of this book, you'll have the confidence and skills to analyze financial data with Python for informed investment decisions. Maximize your returns and stay ahead of the competition by leveraging Python for predictive analytics in finance. Learn Essential Skills: Understand how to gather and preprocess financial data, implement predictive models, and visualize your results. Gain expertise in using Python libraries and tools for financial analysis, and perform investment data analytics with Python. Don't miss out on the opportunity to enhance your predictive analytics skills. Get your copy of Python for Predictive Analytics in Finance: Anticipate Market Movements today and start your journey towards financial mastery! Click "Buy Now" to Stay Ahead of the Market with Predictive Analytics Using Python!