BOOKS - PROGRAMMING - JAVA 18 Algorithms And Data Structures
JAVA 18 Algorithms And Data Structures - Poul Klausen 2018 EPUB | AZW3 | PDF bookboon BOOKS PROGRAMMING
ECO~15 kg CO²

1 TON

Views
79799

Telegram
 
JAVA 18 Algorithms And Data Structures
Author: Poul Klausen
Year: 2018
Pages: 375
Format: EPUB | AZW3 | PDF
File size: 19 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Data Visualisation A Handbook for Data Driven Design 2nd Edition
Introduction to Data Science Data Wrangling and Visualization with R, 2nd Edition
Python Data Science Handbook: Essential Tools for Working with Data
Humanities Data in R Exploring Networks, Geospatial Data, Images, and Text, 2nd Edition
Data Centric Artificial Intelligence: A Beginner|s Guide (Data-Intensive Research)
The Data Preparation Journey: Finding Your Way with R (Chapman and Hall CRC Data Science Series)
Tableau for Salesforce Visualise data and generate insights with the leading platforms for data analytics
Data Universe: Organizational Insights with Python: Embracing Data Driven Decision Making
SQL for Data Analysis Advanced Techniques for Transforming Data into Insights (Early Release)
Training Data for Machine Learning Human Supervision from Annotation to Data Science (Final)
Behavioral Data Analysis with R and Python Customer-Driven Data for Real Business Results
Effective Data Science Infrastructure How to make data scientists productive (MEAP Version 7)
Behavioral Data Analysis with R and Python: Customer-Driven Data for Real Business Results
Tableau for Salesforce Visualise data and generate insights with the leading platforms for data analytics
The Real Work of Data Science Turning data into information, better decisions, and stronger organizations
Practical Data Science with SAP Machine Learning Techniques for Enterprise Data, First Edition
Training Data for Machine Learning Human Supervision from Annotation to Data Science (Final)
Data Universe Organizational Insights with Python Embracing Data Driven Decision Making
Python for Data Analysis Data Wrangling with Pandas, NumPy, and IPython, 2nd Edition
Data Mesh Principles, Patterns, Architecture, and Strategies for Data-Driven Decision Making
Big Data, Small Devices Investigating the Natural World Using Real-Time Data
Univariate, Bivariate, and Multivariate Statistics Using R Quantitative Tools for Data Analysis and Data Science
The Self-Service Data Roadmap Democratize Data and Reduce Time to insight (Early Release)
Big Data, Data Mining, and Machine Learning Value Creation for Business Leaders and Practitioners
Learning Data Science Data Wrangling, Exploration, Visualization, and Modeling with Python (Final)
Learning Data Science Data Wrangling, Exploration, Visualization, and Modeling with Python (Final)
Data Universe Organizational Insights with Python Embracing Data Driven Decision Making
R Graphics Essentials for Great Data Visualization +200 Practical Examples You Want to Know for Data Science
Data Science Essentials with R Learn with focus on data manipulation, visualization, and machine learning
Big Data and Analytics for Beginners: Navigating the World of Data-Driven Decision Making
Data Mesh Principles, Patterns, Architecture, and Strategies for Data-Driven Decision Making
Humanities Data in R Exploring Networks, Geospatial Data, Images, and Text, 2nd Edition
Humanizing Big Data: Marketing at the Meeting of Data, Social Science and Consumer Insight
Data Governance The Definitive Guide People, Processes, and Tools to Operationalize Data Trustworthiness
Agile Data Science 2.0 Building Full-Stack Data Analytics Applications with Spark
Handbook of Research on Big Data and the IoT (Advances in Data Mining and Database Management (ADMDM))
Big Data and Hadoop: Fundamentals, tools, and techniques for data-driven success - 2nd Edition
Hands-On Salesforce Data Cloud Implementing and Managing a Real-Time Customer Data Platform
Hands-On Salesforce Data Cloud Implementing and Managing a Real-Time Customer Data Platform
Apache Iceberg The Definitive Guide Data Lakehouse Functionality, Performance, and Scalability on the Data Lake