Ashish Kumar – författare

Pharmaceutical Engineering: A Primer for Advanced Process Development provides a comprehensive, engineering-focused description of pharmaceutical dosage form process development and manufacturing. This volume introduces the most commonly used manufacturing processes for pharmaceutical dosage forms and addresses critical formulation and process parameters that influence drug product process performance and product quality.This is supplemented with detailed descriptions of engineering models as well as tools that can be used to support their development and verification (such as process analytical technology (PAT)) as well as the appropriate utilization of process and equipment knowledge. Typical scale-up challenges inspired by real industrial examples will be presented as well as a review of the latest correlations, theories and models that can form the basis for science-based scale-ups and transfers.

Features engineering principles of pharmaceutical drug product processesIncludes development and scale-up of pharmaceutical drug product processesDefines a robust process via science and engineering-based principles

Corrosion Resistance and Prevention for Sustainable Automotive Manufacturing is an essential resource for readers in academia and industry aiming to stay current with advancements in automotive materials, coatings, and treatments designed to combat corrosion and extend vehicle life. This book consolidates the latest research, industry best practices, and real-world examples, offering an in-depth understanding of the science behind corrosion prevention. It explores pioneering solutions and strategies addressing the demand for reduced environmental impact in production processes and final products. In addition to addressing corrosion resistance, the book provides insights from leading experts in automotive engineering and materials science.It covers sustainable manufacturing practices, innovative treatments, and coating methodologies, making it an indispensable guide for professionals and researchers dedicated to advancing the automotive sector.Includes comprehensive coverage of the latest research and technologies in corrosion resistance and prevention for vehicles and their partsFeatures real-world case studies and examples of successful corrosion-resistant design and manufacturing, providing readers with practical strategies for implementationHighlights sustainability targets and best practices for more environmentally- conscious automotive manufacturing

Revolutionizing Medical Systems using Artificial Intelligence: A Breakthrough in Healthcare provides an overview of various machine learning and deep learning techniques, addressing the needs of patients and the necessity for medical aid at early stages of disease. The book reviews, analyzes, and compares the different methodologies utilized for the prediction and detection of diseases. In addition, it explores the possible deployment of these advancements in medical systems, from paper to practice. With the advent of technology, tele consultation, telemedicine, and mobile health care, it is now possible to provide continuous monitoring of the health of patients.This title fulfills the needs of connected healthcare systems, providing insights into the role of Artificial Intelligence in the prognosis, diagnosis, and analysis of several diseases. It will be a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the challenging field of artificial intelligence in medical systems and diseases.Provides a wide range of coverage for various prediction and segmentation algorithms that are based on machine learning and deep learning technologyCovers various predictive and segmentation algorithms exploited by various medical personnel to improve the accuracy of treatment to the patientsHighlights improvements in quality and efficiency of medical decision-making in the early detection of critical diseases using AI

In today’s era, there is a need for a system that can automate the process of treatment for the patient if medical facilities are out of reach. Smart healthcare can step in to make the patient more self-dependent. 6G with its features can be seen as the future of smart healthcare with IoT and AI.6G-Enabled IoT and AI for Smart Healthcare: Challenges, Impact, and Analysis offers the fundamentals, history, reality, and challenges faced in the smart healthcare industry today. It discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used. The book details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems. The book goes on to presents applications of smart healthcare through various real-world examples and includes chapters on security and privacy in the 6G-enabled and IoT environment, as well as research on the future prospects of the smart healthcare industry.This book:Offers the fundamentals, history, reality, and the challenges faced in the smart healthcare industryDiscusses the concepts, tools, and techniques of smart healthcare as well as the analysis usedDetails the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systemsPresents applications of smart healthcare through various real-world examplesIncludes topics on security and privacy in 6G-enabled IoT, as well as research and future prospectus of the smart healthcare industryInterested readers of this book will include anyone working in or involved in smart healthcare research which includes, but is not limited to healthcare specialists, computer science engineers, electronics engineers, systems engineers, and pharmaceutical practitioners.

In today’s era, there is a need for a system that can automate the process of treatment for the patient if medical facilities are out of reach. Smart healthcare can step in to make the patient more self-dependent. 6G with its features can be seen as the future of smart healthcare with IoT and AI.6G-Enabled IoT and AI for Smart Healthcare: Challenges, Impact, and Analysis offers the fundamentals, history, reality, and challenges faced in the smart healthcare industry today. It discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used. The book details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems. The book goes on to presents applications of smart healthcare through various real-world examples and includes chapters on security and privacy in the 6G-enabled and IoT environment, as well as research on the future prospects of the smart healthcare industry.This book:Offers the fundamentals, history, reality, and the challenges faced in the smart healthcare industryDiscusses the concepts, tools, and techniques of smart healthcare as well as the analysis usedDetails the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systemsPresents applications of smart healthcare through various real-world examplesIncludes topics on security and privacy in 6G-enabled IoT, as well as research and future prospectus of the smart healthcare industryInterested readers of this book will include anyone working in or involved in smart healthcare research which includes, but is not limited to healthcare specialists, computer science engineers, electronics engineers, systems engineers, and pharmaceutical practitioners.

This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also:Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methodsElaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexityIllustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenariosExplores the future research directions for visual tracking by analyzing the real-time applicationsThe book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Phytochemistry in Corrosion Science covers the use of plant extracts/phytochemicals in corrosion mitigation with industrial applications. It explores innovative and characterization approaches toward the utilization of plant extracts and their phytochemicals as potential corrosion inhibitors for several metals and their alloys.Providing a comprehensive overview of the green aspects of plant extracts as corrosion inhibitors, this book discusses the preparation of aqueous and organic phase extracts, and their advantages, disadvantages, and use for different aggressive media. It also examines aqueous and organic extracts that have been successfully used as corrosion inhibitors for various metals and electrolyte combinations.This book will be a useful reference for undergraduate and graduate students and academic researchers in the fields of phytochemistry, corrosion science and engineering, environmental science, chemical engineering, green chemistry, and mechanical/industrial engineering.

Phytochemistry in Corrosion Science covers the use of plant extracts/phytochemicals in corrosion mitigation with industrial applications. It explores innovative and characterization approaches toward the utilization of plant extracts and their phytochemicals as potential corrosion inhibitors for several metals and their alloys.Providing a comprehensive overview of the green aspects of plant extracts as corrosion inhibitors, this book discusses the preparation of aqueous and organic phase extracts, and their advantages, disadvantages, and use for different aggressive media. It also examines aqueous and organic extracts that have been successfully used as corrosion inhibitors for various metals and electrolyte combinations.This book will be a useful reference for undergraduate and graduate students and academic researchers in the fields of phytochemistry, corrosion science and engineering, environmental science, chemical engineering, green chemistry, and mechanical/industrial engineering.

This book covers all the recent advancements and technologies developed for encapsulated corrosion inhibitors-based coatings by using eco-benign and sustainable encapsulated smart coatings based on self-healing functionality. It includes overview of properties and applicability of encapsulated inhibitors, methodologies to detect corrosion, and recent developments made in the field of corrosion science to study the inhibition potential of encapsulated corrosion inhibitors for eco-benign smart coatings in several corrosive systems.Features:Covers encapsulation of the corrosion inhibitor which explores the self-healing mechanism of the smart coatings.Includes encapsulated corrosion inhibitor fabrication, synthesis, modeling, functionalization, classification, characteristics, and so forth.Reviews effectiveness and significant constraints of scale-up engineering.Discusses the fundamental characteristics of industrial-scale application research for encapsulated corrosion inhibitors.Explores entire aspects of encapsulated corrosion inhibitors-based sustainable smart coatings in one place.This book is aimed at researchers and graduate students of corrosion engineering, surface engineering, and chemistry engineering.

This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also:Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methodsElaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexityIllustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenariosExplores the future research directions for visual tracking by analyzing the real-time applicationsThe book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

This reference book explores various aspects of visceral leishmaniasis (VL) and post-kala-azar dermal leishmaniasis (PKDL), including their pathophysiology, treatment options, and disease control strategies. The initial chapter provides an overview of VL, its global impact, and pathogenesis. It also examines the development of PKDL from VL, outlining the transition from the acute form of the disease to the chronic dermal condition. The book further explores the symptoms and diagnosis of both VL and PKDL. Furthermore, the book delves into the immunopathogenesis of both VL and PKDL, shedding light on the complex interactions between the parasite and the host immune system. It reviews the impact of environmental factors, particularly the contamination of arsenic and antimony in drinking water, on the progression of the disease. Lastly, the book discusses preventive measures for PKDL and highlights the major challenges in effectively implementing these strategies. This book serves as a useful resource for researchers, healthcare professionals, and policymakers seeking to deepen their understanding of these diseases and develop effective strategies for their prevention and control.Key featuresProvides in-depth coverage of VL and PKDL, including pathogenesis, treatment, and disease control strategiesElucidates the symptoms and diagnostic methods for VL and PKDLOffers insights into the complex immunopathogenesis of VL and PKDL, exploring the interactions between parasites and host immune systemExamines treatment options for both VL and PKDL, including current therapeutic approaches and emerging strategiesReviews the impact of environmental factors, such as arsenic and antimony contamination, on the disease progressionDiscusses preventive measures and challenges in implementing effective strategies for PKDL prevention and control

This book covers all the recent advancements and technologies developed for encapsulated corrosion inhibitors-based coatings by using eco-benign and sustainable encapsulated smart coatings based on self-healing functionality. It includes overview of properties and applicability of encapsulated inhibitors, methodologies to detect corrosion, and recent developments made in the field of corrosion science to study the inhibition potential of encapsulated corrosion inhibitors for eco-benign smart coatings in several corrosive systems.Features:Covers encapsulation of the corrosion inhibitor which explores the self-healing mechanism of the smart coatings.Includes encapsulated corrosion inhibitor fabrication, synthesis, modeling, functionalization, classification, characteristics, and so forth.Reviews effectiveness and significant constraints of scale-up engineering.Discusses the fundamental characteristics of industrial-scale application research for encapsulated corrosion inhibitors.Explores entire aspects of encapsulated corrosion inhibitors-based sustainable smart coatings in one place.This book is aimed at researchers and graduate students of corrosion engineering, surface engineering, and chemistry engineering.

This reference book explores the multifaceted problem of heavy metal contamination in the environment. Through its in-depth analysis, the book provides a thorough overview of the sources and pathways of heavy metals, their persistence in ecosystems, and the resulting health impacts on individuals and ecosystems. The chapters explore the diverse sources of contamination, including industrial activities, mining, agriculture, and urbanization, while examining the types of heavy metals found in the environment and their toxicological properties. The book further reviews the profound health effects associated with heavy metal exposure, such as neurological disorders, developmental abnormalities, carcinogenicity, and organ damage. Furthermore, the book provides insights into risk assessment methodologies, regulatory frameworks, and guidelines aimed at controlling and minimizing heavy metal exposure. It highlights the challenges and gaps in current regulations, identifies potential areas for improvement, and presents analytical techniques for heavy metal analysis and removal. This book is an important source for researchers and professionals working in the fields of environmental science, toxicology, and public health.

This book provides a comprehensive analysis of the application of metal-organic frameworks (MOFs) in corrosion protection, consolidating current knowledge and offering insights into potential future advancements in the field. It explores the methods used to fabricate MOF coatings, discussing their advantages, disadvantages, and suitability for various harsh environments. The book also includes industrial case studies, highlighting real-world applications and providing guidance on the future potential of MOFs as anticorrosive coatings.Features:Explores the function of MOFs as anticorrosive coatings, addressing their characteristics, methods of manufacture, and real-world usesDiscovers how MOF coatings offer superior durability and longevity compared to traditional coatingsOffers step-by-step guidance on choosing the right protective measures for different materials and environmentsDemonstrates binding effectiveness of MOF coatings with different metallic surfaces using experimental and computational approachesReviews the broad applicability of MOF coatings across various industriesThis book is aimed at researchers, graduate students in materials science, corrosion science, and related fields, as well as industry professionals seeking to understand and apply the latest developments in corrosion protection.

This book covers the history, biology, pathogenesis, clinical manifestations, and the latest advancements in diagnosis, treatment, and control strategies against leishmaniasis. Chapter 1 presents the life cycle of Leishmania parasites, focusing on vector biology and transmission dynamics, while elucidating the mechanisms of infection and disease progression. The clinical manifestations of cutaneous, visceral, and mucocutaneous leishmaniasis are examined in detail, alongside the immune response of the host and the evasion strategies by the parasite. It also investigates the genetic and molecular diversity of Leishmania, highlighting their virulence mechanisms, and reviews diagnostic methods from traditional techniques to advanced molecular diagnostics. The chapter also covers the current therapeutic approaches, including potential drugs and combination therapies along with integrated vector management strategies for effective disease control. The book explores preventive measures, community interventions, and public health strategies, addressing challenges in leishmaniasis research and identifying knowledge gaps. It presents real-world applications and outcomes through case studies and clinical trials. This book is useful for researchers and students of infectious diseases, tropical medicine, and parasitology.Key Features:Explores the pathogenesis and epidemiology of leishmaniasis, providing a global perspective on its public health impactDetails the life cycle of Leishmania parasites, focusing on vector biology, transmission dynamics, and mechanisms of infectionExamines the clinical manifestations of cutaneous, visceral, and mucocutaneous leishmaniasis, including the host immune response and parasite evasion strategiesReviews current therapeutic approaches, including potential drugs, combination therapies, and integrated vector management strategies for effective controlPresents preventive measures, community interventions, public health strategies, and the challenges in leishmaniasis research

COMPUTATIONAL INTELLIGENCE IN SUBSTAINABLE RELIABILITY ENGINEERING The book is a comprehensive guide on how to apply computational intelligence techniques for the optimization of sustainable materials and reliability engineering. This book focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in reliability engineering, material design, and manufacturing to ensure sustainability. Computational Intelligence in Sustainable Reliability Engineering unveils applications of different models of evolutionary algorithms in the field of optimization and solves the problems to help the manufacturing industries. Some special features of this book include a comprehensive guide for utilizing computational models for reliability engineering, state-of-the-art swarm intelligence methods for solving manufacturing processes and developing sustainable materials, high-quality and innovative research contributions, and a guide for applying computational optimization on reliability and maintainability theory. The book also includes dedicated case studies of real-life applications related to industrial optimizations. Audience Researchers, industry professionals, and post-graduate students in reliability engineering, manufacturing, materials, and design.

Bring the latest technology to bear in the fight for sustainable agriculture with this timely volume Artificial intelligence (AI) has the potential to revolutionize virtually every area of research and scientific practice, including agriculture. With AI solutions emerging to drive higher yields, produce increased resource efficiency, and foster sustainability, there is an urgent need for a volume outlining this progress and charting its future course. Emerging Smart Agricultural Practices Using Artificial Intelligence meets this need with a deep dive into the rapidly developing intersection of agriculture and artificial intelligence. Taking an interdisciplinary approach which applies data science, computer science, and engineering techniques, the book provides cutting-edge insights on the latest advancements in AI-driven agricultural practices. The result is an absolutely critical tool in the ongoing fight to develop sustainable world agriculture. In addition, this book provides: Case studies and real-world applications of new techniques throughoutDetailed discussion of agricultural applications for AI-driven technologies such as machine learning, computer vision, and data analytics A regional approach showcasing international best practices and addressing the varying needs of farmers worldwideEmerging Smart Agricultural Practices Using Artificial Intelligence is ideal for agricultural professionals and scientists, as well as data scientists, technologists, and agricultural policymakers.

Equip yourself to navigate environmental health with this essential resource that integrates fundamentals with cutting-edge applications and research to provide a definitive guide on how chronic exposure to modern pollutants shapes human biological outcomes and regulatory policy. Environmental toxicology, as a field, has evolved significantly in response to the increasing awareness of how environmental contaminants affect human health. Historically, the focus was primarily on acute poisoning events and high-level exposures, but contemporary research emphasizes chronic low-level exposures and their subtle, yet significant, health effects. This book is a comprehensive exploration of the intricate relationships between environmental contaminants and their effects on human health. It delves deeply into the various types of pollutants present in our environment and examines how these contaminants interact with biological systems. Through detailed discussions on exposure pathways, toxicokinetics, and the mechanisms by which environmental toxicants exert their effects, the book covers a broad spectrum of toxicants, including heavy metals, pesticides, endocrine disruptors, and emerging contaminants like nanomaterials and microplastics. The book also includes advanced discussions on the latest research methodologies and technologies in toxicology, such as omics technologies, in vitro and in vivo models, and computational toxicology. Additionally, it addresses the regulatory frameworks and policies that govern environmental health standards, offering insights into risk assessment and management practices. By combining comprehensive coverage of fundamental concepts with discussions of cutting-edge research and future directions, this book serves as an invaluable resource for anyone interested in the ongoing and future challenges of environmental toxicology and its implications for human health.

The emergence of ChatGPT (a publicly available tool developed by Open AI), along with its underlying technology, generative pretrained transformer (GPT), is leading to a significant expansion of generative AI and is unleashing the possibilities for unimaginable transformations across different business domains. This new volume looks at how AI, and ChatGPT in particular, is revolutionizing the business of business, finance, economics, and marketing, exploring its transformative impact and considering its hands-on practical implications.The chapters look at the broad implications in the different domains and provide illustrations and hands-on practice examples that help to evaluate the merits and demerits of ChatGPT, its inherent constraints, its distinctive traits, and its potential utility for researchers and scholars.In finance, the book offers empirical insight into how an investor can employ ChatGPT and make money with AI and ChatGPT-themed equity investments. The authors also look at AI-enabled detection fraud tools that are revolutionizing security and resource protection of financial institutions, contributing to their integrity and overall financial stability. The book also shows how ChatGPT can provide enhanced information analysis for business startup valuation and profitability.In the economic realm, ChatGPT can offer real-time insights into economic trends, such as forecasting crude oil prices, etc. The volume also looks at the ethical and legal concerns of ChatGPT in marketing communication, how ChatGPT can augment consumer behavior analysis, the use of chatbots and virtual assistants, and more. The book also explores public sentiment of Chat-GPT on platforms such as Twitter, how ChatGPT is changing management education, and more.In business practices, the volume looks at AI integration for firms seeking to remain competitive in the ever-changing corporate world. It explores the applications of AI in human resources and how it is automating and augmenting workplace practices by streamlining many business aspects, including recruitment processes and employee engagement, to name two areas. Also considered is ChatGPT role in shaping AI policies and the regulatory landscape that underscores the importance of ethical and responsible use.The applications and value of ChatGPT in marketing is also looked at, such as the ethical and legal concerns of Chat-GPT in marketing communication, using Chat-GPT to analyze customer behavior, using chatbots and virtual assistants for customer service and support services, and more.Highlighting the excellent performance and summary analysis capabilities of ChatGPT, this book presents a compelling synthesis of theoretical perspectives and empirical evidence along with actual examples of successful integration of ChatGPT in marketing, economics, business, and finance.

Understand, evaluate, and visualize dataAbout This Book* Learn basic steps of data analysis and how to use Python and its packages* A step-by-step guide to predictive modeling including tips, tricks, and best practices* Effectively visualize a broad set of analyzed data and generate effective resultsWho This Book Is ForThis book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner.What You Will Learn* Get acquainted with NumPy and use arrays and array-oriented computing in data analysis* Process and analyze data using the time-series capabilities of Pandas* Understand the statistical and mathematical concepts behind predictive analytics algorithms* Data visualization with Matplotlib* Interactive plotting with NumPy, Scipy, and MKL functions* Build financial models using Monte-Carlo simulations* Create directed graphs and multi-graphs* Advanced visualization with D3In DetailYou will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn.After this, you will move on to a data analytics specialization-predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling.After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examplesThis Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan? Learning Predictive Analytics with Python, Ashish Kumar? Mastering Python Data Visualization, Kirthi RamanStyle and approachThe course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization

Gain practical insights by exploiting data in your business to build advanced predictive modeling applicationsKey Features 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 Book Description 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 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 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.