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You'll start with an introduction to hyperparameter tuning and understand why it's important. Next, you'll learn the best methods for hyperparameter tuning for a variety of use cases and specific algorithm types. This book will not only cover the usual grid or random search but also other powerful underdog methods. Individual chapters are also dedicated to the three main groups of hyperparameter tuning methods: exhaustive search, heuristic search, Bayesian optimization, and multi-fidelity optimization. Later, you will learn about top frameworks like Scikit, Hyperopt, Optuna, NNI, and DEAP to implement hyperparameter tuning.

You can find lots of information on Kaggle about competing, but it is difficult to know what is relevant and also very expensive in terms of time and effort – so we put all the essential knowledge into one book. Konrad: My favorite part is Chapter 12 on simulation competitions. Reinforcement learning is a field I have been getting into over the last few years – unlike computer vision or NLP, it has yet to reach wider appeal outside academic circles. It was an interesting and educational experience to try and distill what I have learned into a useful introduction to that fascinating domain. Luca: I enjoyed writing about the history of Kaggle and the professional opportunities it offers.

Kim Kardashian has teamed up with Apple on a custom version of the Beats Fit Pro. The new Beats x Kim collab is available in a trio of skin colors, which are meant to either "blend in or stand out," according to Kardashian. They are still just your standard Beats Fit Pro beneath that skin-tone plastic. But don't expect to find them at all the usual locations when they hit retail on August 17th. In-person sales are limited to 10 Apple stores (including 5th Avenue, Regent Street and Champs-Élysées) as well as several fashion chains and department stores.

The layoffs are part of a restructuring that iRobot said will save the company up to $10 million in 2022 and between $30-$40 million in 2023. This was the same day iRobot announced it was being acquired by Amazon for $1.7 billion. However, iRobot said the two events are not related. To better align costs with near-term revenue, part of the restructuring includes shifting certain non-core engineering functions to lower-cost regions and increasing use of iRobot's joint design manufacturing (JDM) partners. "These actions help support the company's near-term priorities to drive innovation by executing on its product roadmaps, optimize inventory levels across all major channels, expand DTC sales and position the business for profitable growth in 2023," iRobot said in its earnings statement.

Recent years brought an increasing interest in the application of machine learning algorithms in e-commerce, omnichannel marketing, and the sales industry. It is not only to the algorithmic advances but also to data availability, representing transactions, users, and background product information. Finding products related in different ways, i.e., substitutes and complements is essential for users' recommendations at the vendor's site and for the vendor - to perform efficient assortment optimization. The paper introduces a novel method for finding products' substitutes and complements based on the graph embedding Cleora algorithm. We also provide its experimental evaluation with regards to the state-of-the-art Shopper algorithm, studying the relevance of recommendations with surveys from industry experts. It is concluded that the new approach presented here offers suitable choices of recommended products, requiring a minimal amount of additional information. The algorithm can be used in various enterprises, effectively identifying substitute and complementary product options.

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Ora Lassila is a Principal Graph Technologist in the Amazon Neptune graph database team. Earlier, he was a Managing Director at State Street, heading their efforts to adopt ontologies and graph databases. Before that, he worked as a technology architect at Pegasystems, as an architect and technology strategist at Nokia Location & Commerce (aka HERE), and prior to that he was a Research Fellow at the Nokia Research Center Cambridge. He was an elected member of the Advisory Board of the World Wide Web Consortium (W3C) in 1998-2013, and represented Nokia in the W3C Advisory Committee in 1998-2002. In 1996-1997 he was a Visiting Scientist at MIT Laboratory for Computer Science, working with W3C and launching the Resource Description Framework (RDF) standard; he served as a co-editor of the RDF Model and Syntax specification.

Why Will It Affect You? How Do You Survive and Thrive through the AI Revolution? How Do You Survive and Thrive through the AI Revolution? "A fresh, thought provoking, entertaining and accessible post pandemic account of the present and future impact of AI and how to live with it, packed full of useful facts and quotable analogies and anecdotes." "A fresh, thought provoking, entertaining and accessible post pandemic account of the present and future impact of AI and how to live with it, packed full of useful facts and quotable analogies and anecdotes."

The consumer goods retail industry is facing a fundamental dilemma. There is no historical data that can guide today's strategy, but market-standard models for pricing and promotions have typically relied on regressing the past. The industry has long leveraged historical data to extrapolate what might work today, and while there may be value in that analysis, what worked yesterday may not fit today's context. If the past two years have taught us anything, it's that "now" is always changing. The dynamics at play in today's environment quickly reveal why the techniques and algorithms the industry has traditionally deployed when it comes to prices and promotions are no longer enough.