{"title":"Tshepo Chris Nokeri","description":null,"products":[{"product_id":"econometrics-and-data-science-book-tshepo-chris-nokeri-9781484274330","title":"Econometrics and Data Science","description":"Get up to speed on the application of machine learning approaches in macroeconomic research. This book brings together economics and data science. Author Tshepo Chris Nokeri begins by introducing you to covariance analysis, correlation analysis, cross-validation, hyperparameter optimization, regression analysis, and residual analysis. In addition, he presents an approach to contend with multi-collinearity. He then debunks a time series model recognized as the additive model. He reveals a technique for binarizing an economic feature to perform classification analysis using logistic regression. He brings in the Hidden Markov Model, used to discover hidden patterns and growth in the world economy. The author demonstrates unsupervised machine learning techniques such as principal component analysis and cluster analysis. Key deep learning concepts and ways of structuring artificial neural networks are explored along with training them and assessing their performance. The Monte Carlo simulation technique is applied to stimulate the purchasing power of money in an economy. Lastly, the Structural Equation Model (SEM) is considered to integrate correlation analysis, factor analysis, multivariate analysis, causal analysis, and path analysis. After reading this book, you should be able to recognize the connection between econometrics and data science. You will know how to apply a machine learning approach to modeling complex economic problems and others  beyond this book. You will know how to circumvent and enhance model performance, together with the practical implications of a machine learning approach in  econometrics, and you will be able to deal with pressing economic problems.    What You Will Learn  Examine complex, multivariate, linear-causal structures through  the path and structural analysis technique, including non-linearity and hidden  states Be familiar with practical applications of machine learning and deep learning in econometrics Understand theoretical  framework and hypothesis development, and techniques for selecting appropriate  models Develop,  test, validate, and improve key supervised (i.e., regression and  classification) and unsupervised (i.e., dimension reduction and cluster  analysis) machine learning models, alongside neural networks, Markov, and SEM  models Represent and interpret data and models      Who This Book Is For Beginning and intermediate data scientists, economists, machine learning engineers, statisticians, and business executives","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":49741378158865,"sku":"NGR9781484274330","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52543536103697,"sku":"NLS9781484274330","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":52995484909841,"sku":"NIN9781484274330","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1484274334.jpg?v=1751211192"},{"product_id":"artificial-intelligence-in-medical-sciences-and-psychology-book-tshepo-chris-nokeri-9781484282168","title":"Artificial Intelligence in Medical Sciences and Psychology","description":"Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques.     The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification.     This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, medical students, and researchers.    What You Will Learn      Apply artificial neural networks when modelling medical data Know the      standard method for Markov decision making and medical data simulation Understand survival      analysis methods for investigating data from a clinical trial Understand medical record categorization Measure personality differences      using psychological models  Who This Book Is For  Machine learning engineers and software engineers working on healthcare-related projects involving AI, including healthcare professionals interested in knowing how AI can improve their work setting","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":49742085259537,"sku":"NGR9781484282168","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ INGRAM","offer_id":52454267486481,"sku":"NLS9781484282168","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":52748957614353,"sku":"NIN9781484282168","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1484282167.jpg?v=1750892573"},{"product_id":"implementing-machine-learning-for-finance-book-tshepo-chris-nokeri-9781484271094","title":"Implementing Machine Learning for Finance","description":"Bring together machine learning (ML) and deep learning (DL) in financial trading, with an emphasis on investment management. This book explains systematic approaches to investment portfolio management, risk analysis, and performance analysis, including predictive analytics using data science procedures. The book introduces pattern recognition and future price forecasting that exerts effects on time series analysis models, such as the Autoregressive Integrated Moving Average (ARIMA) model, Seasonal ARIMA (SARIMA) model, and Additive model, and it covers the Least Squares model and the Long Short-Term Memory (LSTM) model. It presents hidden pattern recognition and market regime prediction applying the Gaussian Hidden Markov Model. The book covers the practical application of the K-Means model in stock clustering. It establishes the practical application of the Variance-Covariance method and Simulation method (using Monte Carlo Simulation) for value at risk estimation. It also includes market direction classification using both the Logistic classifier and the Multilayer Perceptron classifier. Finally, the book presents performance and risk analysis for investment portfolios. By the end of this book, you should be able to explain how algorithmic trading works and its practical application in the real world, and know how to apply supervised and unsupervised ML and DL models to bolster investment decision making and implement and optimize investment strategies and systems.  What You Will Learn  Understand the fundamentals of the financial market and algorithmic trading, as well as supervised and unsupervised learning models that are appropriate for systematic investment portfolio management Know the concepts of feature engineering, data visualization, and hyperparameter optimization Design, build, and test supervised and unsupervised ML and DL models Discover seasonality, trends, and market regimes, simulating a change in the market and investment strategy problems and predicting market direction and prices Structure and optimize an investment portfolio with preeminent asset classes and measure the underlying risk    Who This Book Is For Beginning and intermediate data scientists, machine learning engineers, business executives, and finance professionals (such as investment analysts and traders)","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51029421424913,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51029423948049,"sku":"NIN9781484271094","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52474531250449,"sku":"NLS9781484271094","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1484271092.jpg?v=1750989842"},{"product_id":"data-science-revealed-book-tshepo-chris-nokeri-9781484268698","title":"Data Science Revealed","description":"Beginning-Intermediate user level","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52331802394897,"sku":"NLS9781484268698","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781484268698.jpg?v=1758149508"},{"product_id":"web-app-development-and-real-time-web-analytics-with-python-book-tshepo-chris-nokeri-9781484277829","title":"Web App Development and Real-Time Web Analytics with Python","description":"Learn to develop and deploy dashboards as web apps using the Python programming language, and how to integrate algorithms into web apps.    Author Tshepo Chris Nokeri begins by introducing you to the basics of constructing and styling static and interactive charts and tables before exploring the basics of HTML, CSS, and Bootstrap, including an approach to building web pages with HTML. From there, he’ll show you the key Python web frameworks and techniques for building web apps with them. You’ll then see how to style web apps and incorporate themes, including interactive charts and tables to build dashboards, followed by a walkthrough of creating URL routes and securing web apps. You’ll then progress to more advanced topics, like building machine learning algorithms and integrating them into a web app. The book concludes with a demonstration of how to deploy web apps in prevalent cloud platforms.    Web App Development  and Real-Time Web Analytics with Python isideal for intermediate data scientists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have the knowledge necessary to create added value for your organization, as you will understand how to link front-end and back-end development, including machine learning.    What You Will Learn      Create      interactive graphs and render static graphs into interactive ones Understand      the essentials of HTML, CSS, and Bootstrap Gain      insight into the key Python web frameworks, and how to develop web      applications using them   Develop      machine learning algorithms and integrate them into web apps   Secure      web apps and deploy them to cloud platforms   Who This Book Is For    Intermediate data scientists, machine learning engineers, and web developers.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52473637404945,"sku":"NLS9781484277829","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":53336172757265,"sku":"NIN9781484277829","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781484277829.jpg?v=1759840265"},{"product_id":"data-science-solutions-with-python-book-tshepo-chris-nokeri-9781484277614","title":"Data Science Solutions with Python","description":"Intermediate-Advanced user level","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52542459707665,"sku":"NLS9781484277614","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":53151721783569,"sku":"NIN9781484277614","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781484277614.jpg?v=1760688989"}],"url":"https:\/\/www.worldofbooks.com\/en-gb\/collections\/author-books-by-tshepo-chris-nokeri.oembed","provider":"World of Books ","version":"1.0","type":"link"}