“…This book is intended for scientists, fishing professionals and decision makers. …”

“…The contents of the Research Topic should appeal to psychologists, linguists, philosophers and cognitive scientists, with research interests in a wide range of domains, from language, through reasoning, judgment and decision making, and moral judgment, to epistemology and theory of mind, philosophical logic, and meta-ethics…”

“…Through this project, we expect to open an opportunity for all scientists in the world dedicated to the pathobiology of this major human fungal pathogen to share their knowledge, experience and opinions and assemble their efforts in defining main research axes to progress in our quest of improved antifungal strategies against IA…”

“…Professor Bennett, an economist, has given us a book that should have emerged long ago from the ranks of political scientists. Stifling Political Competition is an interesting and very well-written study full of insights into the election process. …”

“…Andrew Hacker, "The Frenzy about High-Tech Talent", The New York Review of Books, July 9, 2015 The H-1B visa is the gateway for the world’s best and brightest to live and work in the United States as IT professionals, engineers, scientists, professors, doctors, nurses, and researchers. …”

“…What you will learn Explore and apply different interactive data visualization techniques Manipulate plotting parameters and styles to create appealing plots Customize data visualization for different audiences Design data visualizations using interactive libraries Use Matplotlib, Seaborn, Altair and Bokeh for drawing appealing plots Customize data visualization for different scenarios Who this book is for This book intends to provide a solid training ground for Python developers, data analysts and data scientists to enable them to present critical data insights in a way that best captures the user's attention and imagination. …”

“…What you will learn Apply regression methods to your data and understand how the regression algorithm works Understand the basic concepts of classification methods and how to implement them in the Keras environment Import and organize data for neural network classification analysis Learn about the role of rectified linear units in the Keras network architecture Implement a recurrent neural network to classify the sentiment of sentences from movie reviews Set the embedding layer and the tensor sizes of a network Who this book is for If you are a data scientist, machine learning engineer, deep learning practitioner or an AI engineer who wants to build speedy intelligent applications with minimal lines of codes, then this book is the best fit for you. …”

“…What you will learn Structure a GAN architecture in pseudocode Understand the common architecture for each of the GAN models you will build Implement different GAN architectures in TensorFlow and Keras Use different datasets to enable neural network functionality in GAN models Combine different GAN models and learn how to fine-tune them Produce a model that can take 2D images and produce 3D models Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. …”

“…What you will learn Understand the basics of meta learning methods, algorithms, and types Build voice and face recognition models using a siamese network Learn the prototypical network along with its variants Build relation networks and matching networks from scratch Implement MAML and Reptile algorithms from scratch in Python Work through imitation learning and adversarial meta learning Explore task agnostic meta learning and deep meta learning Who this book is for Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. …”

“…You'll even learn to design your own data structures for projects that require a custom solution. what's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms about the audience For intermediate programmers. about the author Marcello La Rocca is a research scientist and a full-stack engineer. His focus is on optimization algorithms, genetic algorithms, machine learning, and quantum computing. …”

“…If you are a Microsoft Azure data engineer, data scientist, database and BI developer, database administrator, data analyst, or similar profile, then this course will help you further in your professional venture. …”

“…--Gerald Ledford, Senior Research Scientist, Center for Effective Organizations, Marshall School of Business, University of Southern California " The Crowdsourced Performance Review should be at the top of every HR professional's reading list. …”

“…Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. …”

“…Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. …”

“…Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. …”

“…Create your own estimator with the simple syntax of sklearn Explore the feed-forward neural networks available in scikit-learn In Detail Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. …”

“…Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility; moreover, within the Python data space, scikit-learn is the unequivocal choice for machine learning. …”

“…What you will learn Become well versed with recipes that will help you interpret plots with R Formulate advanced statistical models in R to understand its concepts Perform Bayesian regression to predict models and input missing data Use time series analysis for modelling and forecasting temporal data Implement a range of regression techniques for efficient data modelling Get to grips with robust statistics and hidden Markov models Explore ANOVA (Analysis of Variance) and perform hypothesis testing Who this book is for If you are a quantitative researcher, statistician, data analyst, or data scientist looking to tackle various challenges in statistics, this book is what you need! …”

“…First published in 2013, this new edition features full-color photos and shares David's latest insights and experiences as he continues to grow as a maker entrepreneur and citizen scientist…”

“…What you will learn Learn how to compute and visualize marketing KPIs in Python and R Master what drives successful marketing campaigns with data science Use machine learning to predict customer engagement and lifetime value Make product recommendations that customers are most likely to buy Learn how to use A/B testing for better marketing decision making Implement machine learning to understand different customer segments Who this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! …”