Cameron Dodd - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Fundamentals of Analytics Engineering. An introduction to building end-to-end analytics solutions
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Specyfikacja wymagań oprogramowania. Kluczowe praktyki analizy biznesowej
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Learn PostgreSQL. Use, manage, and build secure and scalable databases with PostgreSQL 16 - Second Edition
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Data Curious
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CompTIA Data+: DAO-001 Certification Guide. Complete coverage of the new CompTIA Data+ (DAO-001) exam to help you pass on the first attempt
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The TensorFlow Workshop. A hands-on guide to building deep learning models from scratch using real-world datasets
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Communicating with Data
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Tableau Prep: Up & Running
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The Applied TensorFlow and Keras Workshop. Develop your practical skills by working through a real-world project and build your own Bitcoin price prediction tracker
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The Deep Learning with Keras Workshop. Learn how to define and train neural network models with just a few lines of code
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Algorytmy dla bystrzaków
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Python Deep Learning. Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow - Second Edition
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Hands-On Data Science with R. Techniques to perform data manipulation and mining to build smart analytical models using R
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PostgreSQL 11 Server Side Programming Quick Start Guide. Effective database programming and interaction
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MicroStrategy Quick Start Guide. Data analytics and visualizations for Business Intelligence
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Python Data Science Essentials. A practitioner’s guide covering essential data science principles, tools, and techniques - Third Edition
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Pentaho Data Integration Quick Start Guide. Create ETL processes using Pentaho
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Mastering Numerical Computing with NumPy. Master scientific computing and perform complex operations with ease
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Hands-On Automated Machine Learning. A beginner's guide to building automated machine learning systems using AutoML and Python
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TensorFlow Deep Learning Projects. 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
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Feature Engineering for Machine Learning. Principles and Techniques for Data Scientists
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Learning Pentaho Data Integration 8 CE. An end-to-end guide to exploring, transforming, and integrating your data across multiple sources - Third Edition
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ROS Robotics By Example. Learning to control wheeled, limbed, and flying robots using ROS Kinetic Kame - Second Edition
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Python. Podstawy nauki o danych. Wydanie II
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Deep Learning with TensorFlow. Explore neural networks with Python
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Go Design Patterns. Best practices in software development and CSP
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Scala: Guide for Data Science Professionals. Build robust data pipelines with Scala
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Python: Real World Machine Learning. Take your Python Machine learning skills to the next level
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Python Data Science Essentials. Learn the fundamentals of Data Science with Python - Second Edition
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Understanding Compression. Data Compression for Modern Developers
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Regression Analysis with Python. Discover everything you need to know about the art of regression analysis with Python, and change how you view data
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Creating a Data-Driven Organization
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Mastering matplotlib. A practical guide that takes you beyond the basics of matplotlib and gives solutions to plot complex data
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Learning D3.js Mapping. Build stunning maps and visualizations using D3.js
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Badanie danych. Raport z pierwszej linii działań
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Mastering D3.js. Bring your data to life by creating and deploying complex data visualizations with D3.js
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Business Models for the Data Economy
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Getting Started with Simulink. Written by an experienced engineer, this book will help you utilize the great user-friendly features of Simulink to advance your modeling, testing, and interfacing skills. Packed with illustrations and step-by-step walkthroughs
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Pentaho Data Integration Beginner's Guide. Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide with this book and ebook - Second Edition
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Doing Data Science. Straight Talk from the Frontline
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On Being a Data Skeptic
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Data Analysis with Polars. Get up and running with Polars to perform effective data analysis with Rust