Introduction to Algorithmic Marketing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Algorithmic Marketing write by Ilya Katsov. This book was released on 2017-12-02. Introduction to Algorithmic Marketing available in PDF, EPUB and Kindle. A comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers. The book covers the main areas of marketing that require programmatic micro-decisioning - targeted promotions and advertisements, eCommerce search, recommendations, pricing, and assortment optimization.
Introduction to Algorithmic Marketing
Introduction to Algorithmic Marketing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Algorithmic Marketing write by Ilya Katsov. This book was released on 2017-12. Introduction to Algorithmic Marketing available in PDF, EPUB and Kindle. A comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers. The book covers the main areas of marketing that require programmatic micro-decisioning - targeted promotions and advertisements, eCommerce search, recommendations, pricing, and assortment optimization.
Algorithmic Marketing with Data-driven Simulations
Algorithmic Marketing with Data-driven Simulations - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Algorithmic Marketing with Data-driven Simulations write by Haifeng Zhang. This book was released on 2017. Algorithmic Marketing with Data-driven Simulations available in PDF, EPUB and Kindle.
AI in Marketing, Sales and Service
AI in Marketing, Sales and Service - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook AI in Marketing, Sales and Service write by Peter Gentsch. This book was released on 2018-10-22. AI in Marketing, Sales and Service available in PDF, EPUB and Kindle. AI and Algorithmics have already optimized and automated production and logistics processes. Now it is time to unleash AI on the administrative, planning and even creative procedures in marketing, sales and management. This book provides an easy-to-understand guide to assessing the value and potential of AI and Algorithmics. It systematically draws together the technologies and methods of AI with clear business scenarios on an entrepreneurial level. With interviews and case studies from those cutting edge businesses and executives who are already leading the way, this book shows you: how customer and market potential can be automatically identified and profiled; how media planning can be intelligently automated and optimized with AI and Big Data; how (chat)bots and digital assistants can make communication between companies and consumers more efficient and smarter; how you can optimize Customer Journeys based on Algorithmics and AI; and how to conduct market research in more efficient and smarter way. A decade from now, all businesses will be AI businesses – Gentsch shows you how to make sure yours makes that transition better than your competitors.
Machine Learning for Algorithmic Trading
Machine Learning for Algorithmic Trading - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning for Algorithmic Trading write by Stefan Jansen. This book was released on 2020-07-31. Machine Learning for Algorithmic Trading available in PDF, EPUB and Kindle. Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
