“…Get this video and you’ll enjoy the opportunity to learn from 122 of the world's best data engineers and data scientists working in Asia and elsewhere at data-centric companies such as Singtel, ShopBack, IHI, Lazada, Mediacorp, Qunar, Cloudera, MapR, Microsoft, Cisco, Teradata, BT Group, Google, IBM, Qubole, StarHub, SKY TV, Capgemini, and NTT Data. …”

“…A comprehensive guide to get you up to speed with the latest developments of practical machine learning with Python and upgrade your understanding of machine learning (ML) algorithms and techniquesKey FeaturesDive into machine learning algorithms to solve the complex challenges faced by data scientists todayExplore cutting edge content reflecting deep learning and reinforcement learning developmentsUse updated Python libraries such as TensorFlow, PyTorch, and scikit-learn to track machine learning projects end-to-endBook DescriptionPython Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). …”

“…Tons of companies are adopting Apache Spark to extract meaning from massive data sets, today you have access to that same big data technology right on your desktop.Apache Spark is becoming a must tool for big data engineers and data scientists. In Detail This course covers all the fundamentals of Apache Spark with Scala and teaches you everything you need to know about developing Spark applications with Scala. …”

“…One-stop solution for NLP practitioners, ML developers, and data scientists to build effective NLP systems that can perform real-world complicated tasksKey FeaturesApply deep learning algorithms and techniques such as BiLSTMS, CRFs, BPE and more using TensorFlow 2Explore applications like text generation, summarization, weakly supervised labelling and moreRead cutting edge material with seminal papers provided in the GitHub repository with full working codeBook DescriptionRecently, there have been tremendous advances in NLP, and we are now moving from research labs into practical applications. …”

“…In this course, you'll get a detailed overview of Kotlin and discover why it's becoming the go-to practical language of choice for production-oriented data scientists and engineers. Learners should have Intellij IDEA and JDK, Python experience, and a little experience with basic analytics (Pandas, R, Excel, SQL, etc.). …”

“…A new disease is emerging as the leading killer of North Americans: Scientists are predicting that within eight years, brain disease will kill or disable more people than cancer and heart disease combined. …”

“…Only in recent years have scientists acknowledged the importance of this topic. …”

“…Whilst Jung and his compatriots in related schools of “depth psychology” spoke of “the unconscious” as the driving instinctual force of the mind, scientists today refer principally to the “brain” and its neurological functions and processes. …”

“…However, as a result of differing interpretations of the foundational assumption and dramatically divergent views of the meaning of the term information processing, three separate schools emerged: classical cognitive science, connectionist cognitive science, and embodied cognitive science.Examples, cases, and research findings taken from the wide range of phenomena studied by cognitive scientists effectively explain and explore the relationship among the three perspectives. …”

“…Data Engineering hat sich in den letzten zehn Jahren rasant entwickelt, sodass viele Software Engineers, Datenanalystinnen und Data Scientists nach einer zusammenfassenden Darstellung der grundlegenden Techniken suchen. …”

“…The first three chapters provide an overview of the communication system in technology, present the author's research methods, and describe differences in the career paths and goals of engineers and scientists that cause special problems for organizations. …”

“…"Featuring seventeen original essays on the ethics of Artificial Intelligence (AI) by some of the most prominent AI scientists and academic philosophers today, this volume represents the state-of-the-art thinking in this fast-growing field and highlights some of the central themes in AI and morality such as how to build ethics into AI, how to address mass unemployment as a result of automation, how to avoiding designing AI systems that perpetuate existing biases, and how to determine whether an AI is conscious. …”

“…Conclusion -- Bibliography of Contemporary Works on Scientific Models "Scientists have used models for hundreds of years as a means of describing phenomena and as a basis tor further analogy. …”

“…Presentación del editor: "Almost no systematic theorizing is generality-free. Scientists test general hypotheses; set theorists prove theorems about every set; metaphysicians espouse theses about all things regardless of their kind. …”

“…We are merely the accumulation of tens of thousands of intricate molecular accidents. Some scientists take this logic one step further, suggesting that evolution is intrinsically atheistic and goes against the concept of God. …”

“…Although the particular way to work of the Maestro, selecting a pleiade of brilliant collaborators with whom accomplish such a titanic feat, giving them freedom for their studies, has been recognised and confronted to antagonic systems followed by other relevant scientists and scientific schools, the general recognition of such a significant major milestones for Neuroscience and their vigency in the well-marched XXIst century is not: this is the purpose of this Ebook, to remind all these examples of how successful can be the scientific work when it is minutious, constant and performed by brilliant, imaginative and skilled scientists with a minimal conditions supporting their efforts…”

“…Marc Kilgur, American Scientist (1984) "Brams has performed a service in deominstrating that rational analysis need not stop where issues involving faith and emotion begin." - Peter Bennett, New Scientist (1 March, 1984) "Does game-theoretic theory exist? …”

“…This will facilitate a scientific exchange among individual scientists and groups studying different aspects of communication under adverse conditions and/or the role of cognition in communication. …”

“…And you don't have to be a mathematics expert or a senior data scientist to grasp what's going on inside a deep learning system. …”

“…What you will learn Understand MLOps and deep learning life cycle development Track deep learning models, code, data, parameters, and metrics Build, deploy, and run deep learning model pipelines anywhere Run hyperparameter optimization at scale to tune deep learning models Build production-grade multi-step deep learning inference pipelines Implement scalable deep learning explainability as a service Deploy deep learning batch and streaming inference services Ship practical NLP solutions from experimentation to production Who this book is for This book is for machine learning practitioners including data scientists, data engineers, ML engineers, and scientists who want to build scalable full life cycle deep learning pipelines with reproducibility and provenance tracking using MLflow. …”