Vom kleinen mittelständischen Unternehmen bis hin zum Großkonzern: Wer eine Datenbank sucht, die auf unterschiedlichen Plattformen vor allem zuverlässig laufen soll, der stößt unweigerlich auf "FileMaker Pro".
Vom kleinen mittelständischen Unternehmen bis hin zum Großkonzern: Wer eine App sucht, über die man auf unterschiedlichen Plattformen ausgesuchte Datenbestände abrufen kann, der stößt unweigerlich auf "FileMaker".
Man kennt zwar heute geeignete Methoden, Unstimmigkeiten im Datenbestand zu vermeiden, mit denen man sowohl kleine als auch große Datenstände optimal strukturieren und verwalten kann.
This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques.
Although change is constant in business and analytics, some fundamental principles and lessons learned are truly timeless, extending and surviving beyond the rapid ongoing evolution of tools, techniques, and technologies.
Integrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problemsKey FeaturesDelve into machine learning with this comprehensive guide to scikit-learn and scientific PythonMaster the art of data-driven problem-solving with hands-on examplesFoster your theoretical and practical knowledge of supervised and unsupervised machine learning algorithmsBook DescriptionMachine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners.
An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithmsKey FeaturesExplore statistics and complex mathematics for data-intensive applicationsDiscover new developments in EM algorithm, PCA, and bayesian regressionStudy patterns and make predictions across various datasetsBook DescriptionMachine learning has gained tremendous popularity for its powerful and fast predictions with large datasets.
Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing.
Master powerful strategies to acquire and analyze evidence from real-life scenariosAbout This BookA straightforward guide to address the roadblocks face when doing mobile forensicsSimplify mobile forensics using the right mix of methods, techniques, and toolsGet valuable advice to put you in the mindset of a forensic professional, regardless of your career level or experienceWho This Book Is ForThis book is for forensic analysts and law enforcement and IT security officers who have to deal with digital evidence as part of their daily job.
Find, explore, and extract big data to transform into actionable insightsKey FeaturesPerform end-to-end data analysis-from exploration to visualizationReal-world examples, tasks, and interview queries to be a proficient data scientistUnderstand how SQL is used for big data processing using HiveQL and SparkSQLBook DescriptionSQL Server is a relational database management system that enables you to cover end-to-end data science processes using various inbuilt services and features.
An expert guide to implementing fast, secure, and scalable decentralized applications that work with thousands of users in real timeKey FeaturesImplement advanced features of the Ethereum network to build powerful decentralized applicationsBuild smart contracts on different domains using the programming techniques of Solidity and VyperExplore the architecture of Ethereum network to understand advanced use cases of blockchain development Book DescriptionEthereum is one of the commonly used platforms for building blockchain applications.
Discover how to describe your data in detail, identify data issues, and find out how to solve them using commonly used techniques and tips and tricksKey FeaturesGet well-versed with various data cleaning techniques to reveal key insightsManipulate data of different complexities to shape them into the right form as per your business needsClean, monitor, and validate large data volumes to diagnose problems before moving on to data analysisBook DescriptionGetting clean data to reveal insights is essential, as directly jumping into data analysis without proper data cleaning may lead to incorrect results.
Solve all big data problems by learning how to create efficient data modelsKey FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook DescriptionModeling and managing data is a central focus of all big data projects.
Solve real-world business problems by learning how to create common industry key performance indicators and other calculations using DAX within Microsoft products such as Power BI, SQL Server, and Excel.
Learn how to quickly generate business intelligence, insights and create interactive dashboards for digital storytelling through various data sources with RedashKey FeaturesLearn the best use of visualizations to build powerful interactive dashboardsCreate and share visualizations and data in your organizationWork with different complexities of data from different data sourcesBook DescriptionData exploration and visualization is vital to Business Intelligence, the backbone of almost every enterprise or organization.
Enhance your simulation modeling skills by creating and analyzing digital prototypes of a physical model using Python programming with this comprehensive guideKey FeaturesLearn to create a digital prototype of a real model using hands-on examplesEvaluate the performance and output of your prototype using simulation modeling techniquesUnderstand various statistical and physical simulations to improve systems using PythonBook DescriptionSimulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world.
Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using PythonKey FeaturesBuild a strong foundation in algorithmic trading by becoming well-versed with the basics of financial marketsDemystify jargon related to understanding and placing multiple types of trading ordersDevise trading strategies and increase your odds of making a profit without human interventionBook DescriptionIf you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help.
Reinforce your understanding of data science and data analysis from a statistical perspective to extract meaningful insights from your data using Python programmingKey FeaturesWork your way through the entire data analysis pipeline with statistics concerns in mind to make reasonable decisionsUnderstand how various data science algorithms functionBuild a solid foundation in statistics for data science and machine learning using Python-based examplesBook DescriptionStatistics remain the backbone of modern analysis tasks, helping you to interpret the results produced by data science pipelines.
A practical blockchain handbook designed to take you through implementing and re-engineering banking and financial solutions and workflows using eight step-by-step projectsKey FeaturesImplement various end-to-end blockchain projects and learn to enhance present-day financial solutionsUse Ethereum, Hyperledger, and Stellar to build public and private decentralized applicationsAddress complex challenges faced in the BFSI domain using different blockchain platform servicesBook DescriptionBlockchain technology will continue to play an integral role in the banking and finance sector in the coming years.
Updated and revised second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problemsKey FeaturesUpdated to include new algorithms and techniquesCode updated to Python 3.
Leverage the power of Python and statistical modeling techniques for building accurate predictive modelsKey FeaturesGet introduced to Python's rich suite of libraries for statistical modelingImplement regression, clustering and train neural networks from scratchIncludes real-world examples on training end-to-end machine learning systems in PythonBook DescriptionPython's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today.
A step-by-step approach to building stunning dashboards with QlikViewKey FeaturesPerform effective storytelling through interactive dashboards built with QlikViewCreate different types of visualizations from a variety of data sourcesIncludes tips, tricks, and best practices to perform effective Business Intelligence using QlikViewBook DescriptionQlikView is one of the market leaders when it comes to building effective Business Intelligence solutions.
Understand how blockchain works and explore a variety of strategies to implement it in your organization effectivelyKey FeaturesBecome familiar with business challenges faced by companies when using blockchainDiscover how companies implement blockchain to monetize and secure their dataStudy real-world examples to understand blockchain and its use in organizationsBook DescriptionIn addition to cryptocurrencies, blockchain-based apps are being developed in different industries such as banking, supply chain, and healthcare to achieve digital transformation and enhance user experience.
Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problemsKey FeaturesGain a comprehensive overview of different machine learning techniquesExplore various methods for selecting a particular algorithmImplement a machine learning project from problem definition through to the final modelBook DescriptionWith huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed.
A complete guide to understanding, developing, and testing popular security-token smart contractsKey FeaturesUnderstand key Blockchain and Ethereum platforms conceptsStep-by-step guide to developing STO smart contracts on EthereumMonetize digital tokens under various U.
This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and ClusteringKey FeaturesYour handy guide to building machine learning workflows in Go for real-world scenariosBuild predictive models using the popular supervised and unsupervised machine learning techniquesLearn all about deployment strategies and take your ML application from prototype to production readyBook DescriptionMachine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology.
Learn how to make the right decisions for your business with the help of Python recipes and the expertise of data leadersKey FeaturesLearn and practice various clustering techniques to gather market insights Explore real-life use cases from the business world to contextualize your learningWork your way through practical recipes that will reinforce what you have learnedBook DescriptionOne of the most valuable contributions of data science is toward helping businesses make the right decisions.
Supercharge your skills for developing powerful deep learning models and distributing them at scale efficiently using cloud servicesKey FeaturesUnderstand how to execute a deep learning project effectively using various tools availableLearn how to develop PyTorch and TensorFlow models at scale using Amazon Web ServicesExplore effective solutions to various difficulties that arise from model deploymentBook DescriptionMachine learning engineers, deep learning specialists, and data engineers encounter various problems when moving deep learning models to a production environment.
Take your Python text processing skills to another level by learning about the latest natural language processing and machine learning techniques with this full color guideKey FeaturesLearn how to acquire and process textual data and visualize the key findingsObtain deeper insight into the most commonly used algorithms and techniques and understand their tradeoffsImplement models for solving real-world problems and evaluate their performanceBook DescriptionWith the ever-increasing demand for machine learning and programming professionals, it's prime time to invest in the field.
Get up and running with machine learning life cycle management and implement MLOps in your organizationKey FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed modelsPerform CI/CD to automate new implementations in ML pipelinesBook DescriptionEngineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.
Get better insights from time-series data and become proficient in model performance analysisKey FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook DescriptionThe Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models.
Take your first steps to becoming a fully qualified data analyst by learning how to explore complex datasetsKey FeaturesMaster each concept through practical exercises and activitiesDiscover various statistical techniques to analyze your dataImplement everything you've learned on a real-world case study to uncover valuable insightsBook DescriptionEvery day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace.
