M. - ebooki
Tytuły autora: M. dostępne w księgarni Ebookpoint
-
Data Modeling with Microsoft Excel. Model and analyze data using Power Pivot, DAX, and Cube functions
-
Data Exploration and Preparation with BigQuery. A practical guide to cleaning, transforming, and analyzing data for business insights
-
Amazon Redshift: The Definitive Guide
-
Practical Data Quality. Learn practical, real-world strategies to transform the quality of data in your organization
-
Building ETL Pipelines with Python. Create and deploy enterprise-ready ETL pipelines by employing modern methods
-
Learning Data Science
-
Data Wrangling on AWS. Clean and organize complex data for analysis
-
AI & Data Literacy. Empowering Citizens of Data Science
-
Graph Data Modeling in Python. A practical guide to curating, analyzing, and modeling data with graphs
-
Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python
-
Geospatial Data Analytics on AWS. Discover how to manage and analyze geospatial data in the cloud
-
Embedded Analytics
-
Streaming Data Mesh
-
CompTIA Data+: DAO-001 Certification Guide. Complete coverage of the new CompTIA Data+ (DAO-001) exam to help you pass on the first attempt
-
Machine Learning in Microservices. Productionizing microservices architecture for machine learning solutions
-
Tomographic imaging in environmental, industrial and medical applications
-
Machine Learning Model Serving Patterns and Best Practices. A definitive guide to deploying, monitoring, and providing accessibility to ML models in production
-
Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
-
Microsoft Power BI Quick Start Guide. The ultimate beginner's guide to data modeling, visualization, digital storytelling, and more - Third Edition
-
Neural Search - From Prototype to Production with Jina. Build deep learning–powered search systems that you can deploy and manage with ease
-
Learning Microsoft Power BI
-
Data Quality Fundamentals
-
Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features
-
SQL for Data Analytics. Harness the power of SQL to extract insights from data - Third Edition
-
Cyfrowe Państwo. Uwarunkowania i perspektywy
-
Data Cleaning and Exploration with Machine Learning. Get to grips with machine learning techniques to achieve sparkling-clean data quickly
-
Simplifying Data Engineering and Analytics with Delta. Create analytics-ready data that fuels artificial intelligence and business intelligence
-
Practical Deep Learning at Scale with MLflow. Bridge the gap between offline experimentation and online production
-
Feature Store for Machine Learning. Curate, discover, share and serve ML features at scale
-
AI-Powered Business Intelligence
-
The Tableau Workshop. A practical guide to the art of data visualization with Tableau
-
Data Algorithms with Spark
-
Getting Started with Amazon SageMaker Studio. Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE
-
Simplify Big Data Analytics with Amazon EMR. A beginner’s guide to learning and implementing Amazon EMR for building data analytics solutions
-
Data Mesh
-
Extreme DAX. Take your Power BI and Microsoft data analytics skills to the next level
-
Digital Transformation and Modernization with IBM API Connect. A practical guide to developing, deploying, and managing high-performance and secure hybrid-cloud APIs
-
The TensorFlow Workshop. A hands-on guide to building deep learning models from scratch using real-world datasets
-
Essential PySpark for Scalable Data Analytics. A beginner's guide to harnessing the power and ease of PySpark 3
-
Digital Transformation with Dataverse for Teams. Become a citizen developer and lead the digital transformation wave with Microsoft Teams and Power Platform
-
Data Engineering with Apache Spark, Delta Lake, and Lakehouse. Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way
-
Deep Learning with fastai Cookbook. Leverage the easy-to-use fastai framework to unlock the power of deep learning
-
Data Analytics Made Easy. Analyze and present data to make informed decisions without writing any code
-
Amazon Redshift Cookbook. Recipes for building modern data warehousing solutions
-
Limitless Analytics with Azure Synapse. An end-to-end analytics service for data processing, management, and ingestion for BI and ML
-
97 Things Every Data Engineer Should Know
-
Mastering Tableau 2021. Implement advanced business intelligence techniques and analytics with Tableau - Third Edition
-
Scalable Data Streaming with Amazon Kinesis. Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis
-
Cleaning Data for Effective Data Science. Doing the other 80% of the work with Python, R, and command-line tools
-
Effortless App Development with Oracle Visual Builder. Boost productivity by building web and mobile applications efficiently using the drag-and-drop approach
-
Managing Microsoft Teams: MS-700 Exam Guide. Configure and manage Microsoft Teams workloads and achieve Microsoft 365 certification with ease
-
Python Data Analysis. Perform data collection, data processing, wrangling, visualization, and model building using Python - Third Edition
-
Python Data Cleaning Cookbook. Modern techniques and Python tools to detect and remove dirty data and extract key insights
-
Codeless Deep Learning with KNIME. Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform
-
Microsoft SQL Server 2012 Analysis Services: Model tabelaryczny BISM
-
Microsoft Power BI Quick Start Guide. Bring your data to life through data modeling, visualization, digital storytelling, and more - Second Edition
-
Deep Learning for Beginners. A beginner's guide to getting up and running with deep learning from scratch using Python
-
The Self-Service Data Roadmap
-
The Data Science Workshop. Learn how you can build machine learning models and create your own real-world data science projects - Second Edition
-
Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
-
The Data Visualization Workshop. A self-paced, practical approach to transforming your complex data into compelling, captivating graphics
-
The Computer Vision Workshop. Develop the skills you need to use computer vision algorithms in your own artificial intelligence projects
-
Practical Data Analysis Using Jupyter Notebook. Learn how to speak the language of data by extracting useful and actionable insights using Python
-
Practical Synthetic Data Generation. Balancing Privacy and the Broad Availability of Data
-
Hands-On Deep Learning with R. A practical guide to designing, building, and improving neural network models using R
-
Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter. Build scalable real-world projects to implement end-to-end neural networks on Android and iOS
-
Hands-On Exploratory Data Analysis with Python. Perform EDA techniques to understand, summarize, and investigate your data
-
The Practitioner's Guide to Graph Data. Applying Graph Thinking and Graph Technologies to Solve Complex Problems
-
The Applied SQL Data Analytics Workshop. Develop your practical skills and prepare to become a professional data analyst - Second Edition
-
The Data Science Workshop. A New, Interactive Approach to Learning Data Science
-
Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition
-
Tableau Desktop Certified Associate: Exam Guide. Develop your Tableau skills and prepare for Tableau certification with tips from industry experts
-
Salesforce Advanced Administrator Certification Guide. Become a Certified Advanced Salesforce Administrator with this exam guide
-
Learn Odoo. A beginner's guide to designing, configuring, and customizing business applications with Odoo
-
Mastering pandas. A complete guide to pandas, from installation to advanced data analysis techniques - Second Edition
-
Elasticsearch 7 Quick Start Guide. Get up and running with the distributed search and analytics capabilities of Elasticsearch
-
R Bioinformatics Cookbook. Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis
-
arc42 by Example. Software architecture documentation in practice
-
Hands-On Internet of Things with MQTT. Build connected IoT devices with Arduino and MQ Telemetry Transport (MQTT)
-
Binary Analysis Cookbook. Actionable recipes for disassembling and analyzing binaries for security risks
-
SQL for Data Analytics. Perform fast and efficient data analysis with the power of SQL
-
Hands-On Data Analysis with Pandas. Efficiently perform data collection, wrangling, analysis, and visualization using Python
-
Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
-
Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R
-
Hands-On Deep Learning Architectures with Python. Create deep neural networks to solve computational problems using TensorFlow and Keras
-
Hands-On Deep Learning for Games. Leverage the power of neural networks and reinforcement learning to build intelligent games
-
Natural Language Processing Fundamentals. Build intelligent applications that can interpret the human language to deliver impactful results
-
Hands-On Big Data Analytics with PySpark. Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs
-
Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide. A practical guide to building neural networks using Microsoft's open source deep learning framework
-
Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
-
Learning Tableau 2019. Tools for Business Intelligence, data prep, and visual analytics - Third Edition
-
Hands-On Business Intelligence with Qlik Sense. Implement self-service data analytics with insights and guidance from Qlik Sense experts
-
Mastering Tableau 2019.1. An expert guide to implementing advanced business intelligence and analytics with Tableau 2019.1 - Second Edition
-
Mastering Hadoop 3. Big data processing at scale to unlock unique business insights
-
Hands-On Deep Learning with Apache Spark. Build and deploy distributed deep learning applications on Apache Spark
-
Machine Learning Quick Reference. Quick and essential machine learning hacks for training smart data models
-
Hands-On Data Science with the Command Line. Automate everyday data science tasks using command-line tools
-
Tableau 2019.x Cookbook. Over 115 recipes to build end-to-end analytical solutions using Tableau
-
Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics
-
Mastering Machine Learning with R. Advanced machine learning techniques for building smart applications with R 3.5 - Third Edition
-
Apache Spark Quick Start Guide. Quickly learn the art of writing efficient big data applications with Apache Spark
-
Hands-On Artificial Intelligence for IoT. Expert machine learning and deep learning techniques for developing smarter IoT systems
-
Advanced MySQL 8. Discover the full potential of MySQL and ensure high performance of your database
-
Go Web Scraping Quick Start Guide. Implement the power of Go to scrape and crawl data from the web
-
Blockchain Quick Start Guide. A beginner's guide to developing enterprise-grade decentralized applications
-
QlikView: Advanced Data Visualization. Discover deeper insights with Qlikview by building your own rich analytical applications from scratch
-
Bayesian Analysis with Python. Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ - Second Edition
-
Principles of Data Science. Understand, analyze, and predict data using Machine Learning concepts and tools - Second Edition
-
Tableau 10 Complete Reference. Transform your business with rich data visualizations and interactive dashboards with Tableau 10
-
Apache Spark 2: Data Processing and Real-Time Analytics. Master complex big data processing, stream analytics, and machine learning with Apache Spark
-
Numerical Computing with Python. Harness the power of Python to analyze and find hidden patterns in the data
-
Microsoft Power BI Complete Reference. Bring your data to life with the powerful features of Microsoft Power BI
-
Hands-On Geospatial Analysis with R and QGIS. A beginner’s guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2
-
Julia 1.0 Programming Cookbook. Over 100 numerical and distributed computing recipes for your daily data science work?ow
-
Splunk 7.x Quick Start Guide. Gain business data insights from operational intelligence
-
Mastering Matplotlib 2.x. Effective Data Visualization techniques with Python
-
Hands-On Data Science with SQL Server 2017. Perform end-to-end data analysis to gain efficient data insight
-
Getting Started with Haskell Data Analysis. Put your data analysis techniques to work and generate publication-ready visualizations