eBooki
W kategorii eBooki znajdziesz książki w postaci elektronicznej, w formie PDF, ePub oraz mobi. Po zakupie e-booka będzie on dostępny w Bibliotece na koncie użytkownika. Książki przeczytasz na laptopie, tablecie, smartfonie lub czytniku ebooków (Kindle, Pocketbook, inkBOOK, Prestigio i innych). Więcej na temat wykorzystania i zabezpieczenia eBooków znajdziesz na stronie "Przewodnik po eBookach".
Ebooki dostępne w księgarni Ebookpoint
-
Apache Mahout Essentials. Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout
-
Learning Bayesian Models with R. Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems
-
Practical Data Analysis. Pandas, MongoDB, Apache Spark, and more - Second Edition
-
Mastering Probabilistic Graphical Models Using Python. Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python
-
Monitoring Docker. Monitor your Docker containers and their apps using various native and third-party tools with the help of this exclusive guide!
-
Python Data Analysis Cookbook. Clean, scrape, analyze, and visualize data with the power of Python!
-
IPython Interactive Computing and Visualization Cookbook. Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes
-
Learning NumPy Array. Supercharge your scientific Python computations by understanding how to use the NumPy library effectively
-
Splunk Operational Intelligence Cookbook. Transform Big Data into business-critical insights and rethink operational Intelligence with Splunk - Second Edition
-
Mastering Python Scientific Computing. A complete guide for Python programmers to master scientific computing using Python APIs and tools
-
Python 3 Text Processing with NLTK 3 Cookbook
-
Real-time Analytics with Storm and Cassandra. Solve real-time analytics problems effectively using Storm and Cassandra
-
Mastering D3.js. Bring your data to life by creating and deploying complex data visualizations with D3.js
-
Building Machine Learning Systems with Python. Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need
-
Practical Data Analysis. For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that
-
Data Analysis with Stata. Explore the big data field and learn how to perform data analytics and predictive modelling in STATA
-
QlikView for Developers Cookbook. Take your QlikView training to the next level with this brilliant book that's packed with recipes which progress from intermediate to advanced. The step-by step-approach makes learning easy and enjoyable
-
Python: Data Analytics and Visualization. Perform data processing and analysis with the help of python libraries, gain practical insights into predictive modeling and generate effective results in a variety of visually appealing charts using the plotting packages in Python
-
matplotlib Plotting Cookbook. Discover how easy it can be to create great scientific visualizations with Python. This cookbook includes over sixty matplotlib recipes together with clarifying explanations to ensure you can produce plots of high quality
-
Mathematica Data Visualization. Create and prototype interactive data visualizations using Mathematica
-
Python: Real-World Data Science. Real-World Data Science
-
Simulation for Data Science with R. Effective Data-driven Decision Making
-
Learning Predictive Analytics with Python. Click here to enter text
-
Data Augmentation with Python. Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data
-
Data Ingestion with Python Cookbook. A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process
-
Data Modeling with Snowflake. A practical guide to accelerating Snowflake development using universal data modeling techniques
-
Graph Data Modeling in Python. A practical guide to curating, analyzing, and modeling data with graphs
-
Data Engineering with dbt. A practical guide to building a cloud-based, pragmatic, and dependable data platform with SQL
-
Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python
-
Driving Data Quality with Data Contracts. A comprehensive guide to building reliable, trusted, and effective data platforms
-
Geospatial Data Analytics on AWS. Discover how to manage and analyze geospatial data in the cloud
-
Natural Language Understanding with Python. Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems
-
Exploratory Data Analysis with Python Cookbook. Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
-
AI & Data Literacy. Empowering Citizens of Data Science
-
Modern Data Architectures with Python. A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python
-
Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition
-
De-Mystifying Math and Stats for Machine Learning. Mastering the Fundamentals of Mathematics and Statistics for Machine Learning
-
Algorithms and Data Structures with Python. A comprehensive guide to data structures & algorithms via an interactive learning experience
-
Data Analysis Foundations with Python. Master Data Analysis with Python: From Basics to Advanced Techniques
-
Generative Deep Learning with Python. Unleashing the Creative Power of AI by Mastering AI and Python
-
Introduction to Algorithms. A Comprehensive Guide for Beginners: Unlocking Computational Thinking
-
The Culture of Big Data
-
Building Data Science Teams
-
Real-Time Big Data Analytics: Emerging Architecture
-
Planning for Big Data
-
Data Jujitsu: The Art of Turning Data into Product
-
How Data Science Is Transforming Health Care
-
What Is Data Science?
-
Big Data Now: 2012 Edition. 2nd Edition
-
Big Data Now: Current Perspectives from O'Reilly Radar
-
Business Models for the Data Economy
-
Disruptive Possibilities: How Big Data Changes Everything
-
The Evolution of Data Products
-
On Being a Data Skeptic
-
Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
-
Data Cleaning and Exploration with Machine Learning. Get to grips with machine learning techniques to achieve sparkling-clean data quickly
-
Neural Search - From Prototype to Production with Jina. Build deep learning–powered search systems that you can deploy and manage with ease
-
Practical Deep Learning at Scale with MLflow. Bridge the gap between offline experimentation and online production
-
The Pandas Workshop. A comprehensive guide to using Python for data analysis with real-world case studies
-
Modern Time Series Forecasting with Python. Explore industry-ready time series forecasting using modern machine learning and deep learning
-
Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition
-
Machine Learning Techniques for Text. Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluation
-
CompTIA Data+: DAO-001 Certification Guide. Complete coverage of the new CompTIA Data+ (DAO-001) exam to help you pass on the first attempt
-
Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models - Second Edition
-
Quantum Machine Learning and Optimisation in Finance. On the Road to Quantum Advantage
-
Computer Vision on AWS. Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker
-
The Tableau Workshop. A practical guide to the art of data visualization with Tableau
-
Machine Learning Model Serving Patterns and Best Practices. A definitive guide to deploying, monitoring, and providing accessibility to ML models in production
-
Microsoft Power BI Quick Start Guide. The ultimate beginner's guide to data modeling, visualization, digital storytelling, and more - Third Edition
-
Machine Learning in Microservices. Productionizing microservices architecture for machine learning solutions
-
Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features
-
Scalable Data Architecture with Java. Build efficient enterprise-grade data architecting solutions using Java
-
Feature Store for Machine Learning. Curate, discover, share and serve ML features at scale
-
Data Analytics Using Splunk 9.x. A practical guide to implementing Splunk’s features for performing data analysis at scale
-
The Kaggle Workbook. Self-learning exercises and valuable insights for Kaggle data science competitions
-
Simplifying Data Engineering and Analytics with Delta. Create analytics-ready data that fuels artificial intelligence and business intelligence
-
Robo-Advisor with Python. A hands-on guide to building and operating your own Robo-advisor
-
Applied Geospatial Data Science with Python. Leverage geospatial data analysis and modeling to find unique solutions to environmental problems
-
The Art of Data-Driven Business. Transform your organization into a data-driven one with the power of Python machine learning
-
SQL for Data Analytics. Harness the power of SQL to extract insights from data - Third Edition
-
Graph Data Processing with Cypher. A practical guide to building graph traversal queries using the Cypher syntax on Neo4j
-
Learn Azure Synapse Data Explorer. A guide to building real-time analytics solutions to unlock log and telemetry data
-
Data Wrangling with R. Load, explore, transform and visualize data for modeling with tidyverse libraries
-
Python. Podstawy nauki o danych. Wydanie II
-
Aplikacje ChatGPT. Wejdź na wyższy poziom z inteligentnymi programami - generatory, boty i wiele innych!
-
Uczenie maszynowe z użyciem Scikit-Learn i TensorFlow
-
Uczenie maszynowe w Pythonie. Receptury
-
Uczenie maszynowe dla programistów
-
Zaawansowane uczenie maszynowe z językiem Python
-
Zwinna analiza danych. Apache Hadoop dla każdego
-
Transforming Healthcare with DevOps. A practical DevOps4Care guide to embracing the complexity of digital transformation
-
Simplifying Android Development with Coroutines and Flows. Learn how to use Kotlin coroutines and the flow API to handle data streams asynchronously in your Android app
-
Data Analytics with Hadoop. An Introduction for Data Scientists
-
Understanding Compression. Data Compression for Modern Developers
-
Introduction to Machine Learning with Python. A Guide for Data Scientists
-
Programming Pig. Dataflow Scripting with Hadoop. 2nd Edition
-
Practical Machine Learning with H2O. Powerful, Scalable Techniques for Deep Learning and AI
-
Efficient R Programming. A Practical Guide to Smarter Programming
-
Thoughtful Machine Learning with Python. A Test-Driven Approach
-
Designing Data-Intensive Applications. The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
-
Data Science i uczenie maszynowe
-
Advanced Analytics with Spark. Patterns for Learning from Data at Scale. 2nd Edition
-
Deep Learning. A Practitioner's Approach
-
Learning TensorFlow. A Guide to Building Deep Learning Systems
-
Network Security Through Data Analysis. From Data to Action. 2nd Edition
-
Making Data Visual. A Practical Guide to Using Visualization for Insight
-
Machine Learning and Security. Protecting Systems with Data and Algorithms
-
Spark: The Definitive Guide. Big Data Processing Made Simple
-
TensorFlow for Deep Learning. From Linear Regression to Reinforcement Learning
-
Introduction to Machine Learning with R. Rigorous Mathematical Analysis
-
Feature Engineering for Machine Learning. Principles and Techniques for Data Scientists
-
Practical Tableau. 100 Tips, Tutorials, and Strategies from a Tableau Zen Master
-
Deep Learning Cookbook. Practical Recipes to Get Started Quickly
-
Getting Started with Kudu. Perform Fast Analytics on Fast Data
-
R Graphics Cookbook. Practical Recipes for Visualizing Data. 2nd Edition
-
Natural Language Processing with PyTorch. Build Intelligent Language Applications Using Deep Learning
-
The Enterprise Big Data Lake. Delivering the Promise of Big Data and Data Science
-
R Cookbook. Proven Recipes for Data Analysis, Statistics, and Graphics. 2nd Edition
-
Generative Deep Learning. 2nd Edition
-
Streaming Data Mesh