Big data
Książki, ebooki, audiobooki, kursy video z kategorii: Big data dostępne w księgarni Ebookpoint
-
The Machine Learning Solutions Architect Handbook. Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI - Second Edition
-
Excel 2021 i Microsoft 365. Analiza i modelowanie danych biznesowych
-
Data science od podstaw. Analiza danych w Pythonie
-
Microsoft SQL Server. Modelowanie i eksploracja danych
-
Data Governance Handbook. A practical approach to building trust in data
-
Extending Excel with Python and R. Unlock the potential of analytics languages for advanced data manipulation and visualization
-
Data Engineering with Google Cloud Platform. A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud - Second Edition
-
Transformers for Natural Language Processing and Computer Vision. Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3 - Third Edition
-
Machine Learning Security with Azure. Best practices for assessing, securing, and monitoring Azure Machine Learning workloads
-
Robo-Advisor with Python. A hands-on guide to building and operating your own Robo-advisor
-
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
-
The Pandas Workshop. A comprehensive guide to using Python for data analysis with real-world case studies
-
Analiza danych behawioralnych przy użyciu języków R i Python
-
Practical Machine Learning for Computer Vision
-
Distributed Data Systems with Azure Databricks. Create, deploy, and manage enterprise data pipelines
-
Hands-On Reinforcement Learning for Games. Implementing self-learning agents in games using artificial intelligence techniques
-
Java Deep Learning Cookbook. Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j
-
Hands-On Data Analysis with Scala. Perform data collection, processing, manipulation, and visualization with Scala
-
Keras Reinforcement Learning Projects. 9 projects exploring popular reinforcement learning techniques to build self-learning agents
-
Implementing Oracle API Platform Cloud Service. Design, deploy, and manage your APIs in Oracle’s new API Platform
-
Graph Databases. New Opportunities for Connected Data. 2nd Edition
-
Matematyka dyskretna dla praktyków. Algorytmy i uczenie maszynowe w Pythonie
-
Deep Learning. Praktyczne wprowadzenie
-
Architecting Data and Machine Learning Platforms
-
Web scraping. Kurs video. Zautomatyzowane pozyskiwanie danych z sieci
-
Uczenie maszynowe w Pythonie. Receptury
-
Zaawansowane uczenie maszynowe z językiem Python
-
Uczenie maszynowe dla programistów
-
The Definitive Guide to Data Integration. Unlock the power of data integration to efficiently manage, transform, and analyze data
-
Effective Machine Learning Teams
-
Kibana 8.x - A Quick Start Guide to Data Analysis. Learn about data exploration, visualization, and dashboard building with Kibana
-
Web Data Mining z użyciem języka Python. Odkrywaj i wyodrębniaj informacje ze stron internetowych za pomocą języka Python
-
Implementing MLOps in the Enterprise
-
TinyML Cookbook. Combine machine learning with microcontrollers to solve real-world problems - Second Edition
-
Quantum Computing Algorithms. Discover how a little math goes a long way
-
Analityka biznesowa wspomagana sztuczną inteligencją. Ulepszanie prognoz i podejmowania decyzji za pomocą uczenia maszynowego
-
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. 3rd Edition
-
Praktyczne uczenie maszynowe w języku R
-
Data Forecasting and Segmentation Using Microsoft Excel. Perform data grouping, linear predictions, and time series machine learning statistics without using code
-
The Kaggle Book. Data analysis and machine learning for competitive data science
-
Transformers for Natural Language Processing. Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4 - Second Edition
-
Getting Started with Elastic Stack 8.0. Run powerful and scalable data platforms to search, observe, and secure your organization
-
Hands-On Data Analysis with Pandas. A Python data science handbook for data collection, wrangling, analysis, and visualization - Second Edition
-
Microsoft Power Platform Functional Consultant: PL-200 Exam Guide. Learn how to customize and configure Microsoft Power Platform and prepare for the PL-200 exam
-
The Deep Learning with Keras Workshop. Learn how to define and train neural network models with just a few lines of code
-
The Machine Learning Workshop. Get ready to develop your own high-performance machine learning algorithms with scikit-learn - Second Edition
-
The Supervised Learning Workshop. Predict outcomes from data by building your own powerful predictive models with machine learning in Python - Second Edition
-
Python Deep Learning. Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow - Second Edition
-
Python Artificial Intelligence Projects for Beginners. Get up and running with Artificial Intelligence using 8 smart and exciting AI applications
-
Teradata Cookbook. Over 85 recipes to implement efficient data warehousing solutions
-
Building a Recommendation System with R. Learn the art of building robust and powerful recommendation engines using R
-
Data Science for Business. What You Need to Know about Data Mining and Data-Analytic Thinking
-
Analiza danych w zarządzaniu projektami
-
Excel 2013. Kurs video. Poziom drugi. Przetwarzanie i analiza danych
-
Badanie danych. Raport z pierwszej linii działań
-
Excel 2013 PL. Kurs
-
Excel 2010 PL. Ilustrowany przewodnik
-
Analiza i prezentacja danych w Microsoft Excel. Vademecum Walkenbacha
-
100 sposobów na Excel 2007 PL. Tworzenie funkcjonalnych arkuszy
-
Excel 2010 PL. Kurs
-
Sztuczna Inteligencja i Uczenie Maszynowe: Kompletny Przewodnik do Budowy Własnych Rozwiązań AI
-
Practical Lakehouse Architecture
-
Unleashing the Power of Data with Trusted AI. A guide for board members and executives
-
Tableau Certified Data Analyst Certification Guide. Ace the Tableau Data Analyst certification exam with expert guidance and practice material
-
Getting Started with DuckDB. A practical guide for accelerating your data science, data analytics, and data engineering workflows
-
Deep Learning at Scale
-
Introduction to Algorithms. A Comprehensive Guide for Beginners: Unlocking Computational Thinking
-
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
-
Data Modeling with Microsoft Power BI
-
Augmented Analytics
-
Python Data Cleaning Cookbook. Prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn, and OpenAI - Second Edition
-
The Ultimate Guide to Snowpark. Design and deploy Snowpark with Python for efficient data workloads
-
Privacy-Preserving Machine Learning. A use-case-driven approach to building and protecting ML pipelines from privacy and security threats
-
Data Quality in the Age of AI. Building a foundation for AI strategy and data culture
-
Databricks ML in Action. Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment
-
Data Analytics for Marketing. A practical guide to analyzing marketing data using Python
-
Accelerate Model Training with PyTorch 2.X. Build more accurate models by boosting the model training process
-
Active Machine Learning with Python. Refine and elevate data quality over quantity with active learning
-
Engineering Data Mesh in Azure Cloud. Implement data mesh using Microsoft Azure's Cloud Adoption Framework
-
Fundamentals of Analytics Engineering. An introduction to building end-to-end analytics solutions
-
Artificial Intelligence with Microsoft Power BI
-
Machine Learning: Make Your Own Recommender System. Build Your Recommender System with Machine Learning Insights
-
Machine Learning with Python. Unlocking AI Potential with Python and Machine Learning
-
Cracking the Data Science Interview. Unlock insider tips from industry experts to master the data science field
-
Data-Centric Machine Learning with Python. The ultimate guide to engineering and deploying high-quality models based on good data
-
AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide. The ultimate guide to passing the MLS-C01 exam on your first attempt - Second Edition
-
Building Interactive Dashboards in Microsoft 365 Excel. Harness the new features and formulae in M365 Excel to create dynamic, automated dashboards
-
Data Cleaning with Power BI. The definitive guide to transforming dirty data into actionable insights
-
Data Stewardship in Action. A roadmap to data value realization and measurable business outcomes
-
Hands-On Entity Resolution
-
MLOps with Red Hat OpenShift. A cloud-native approach to machine learning operations
-
Principles of Data Science. A beginner's guide to essential math and coding skills for data fluency and machine learning - Third Edition
-
Data Labeling in Machine Learning with Python. Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models
-
Bayesian Analysis with Python. A practical guide to probabilistic modeling - Third Edition
-
Machine Learning Infrastructure and Best Practices for Software Engineers. Take your machine learning software from a prototype to a fully fledged software system
-
Automating Data Quality Monitoring
-
Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet
-
Data Observability for Data Engineering. Proactive strategies for ensuring data accuracy and addressing broken data pipelines
-
Data Science for Web3. A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
-
The Deep Learning Architect's Handbook. Build and deploy production-ready DL solutions leveraging the latest Python techniques
-
Developing Kaggle Notebooks. Pave your way to becoming a Kaggle Notebooks Grandmaster
-
Learn Grafana 10.x. A beginner's guide to practical data analytics, interactive dashboards, and observability - Second Edition
-
Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications
-
Vector Search for Practitioners with Elastic. A toolkit for building NLP solutions for search, observability, and security using vector search
-
Data Modeling with Microsoft Excel. Model and analyze data using Power Pivot, DAX, and Cube functions
-
Machine Learning for Imbalanced Data. Tackle imbalanced datasets using machine learning and deep learning techniques
-
Machine Learning Interviews
-
Data Exploration and Preparation with BigQuery. A practical guide to cleaning, transforming, and analyzing data for business insights
-
Practical Machine Learning on Databricks. Seamlessly transition ML models and MLOps on Databricks
-
Training Data for Machine Learning
-
Cracking the Data Engineering Interview. Land your dream job with the help of resume-building tips, over 100 mock questions, and a unique portfolio
-
Data Science: The Hard Parts
-
Alteryx Designer Cookbook. Over 60 recipes to transform your data into insights and take your productivity to a new level
-
Machine Learning with Qlik Sense. Utilize different machine learning models in practical use cases by leveraging Qlik Sense
-
Synthetic Data for Machine Learning. Revolutionize your approach to machine learning with this comprehensive conceptual guide
-
The Statistics and Machine Learning with R Workshop. Unlock the power of efficient data science modeling with this hands-on guide
-
Delta Lake: Up and Running
-
Amazon Redshift: The Definitive Guide