BOOKS - PROGRAMMING - Machine Learners Archaeology of a Data Practice
Machine Learners Archaeology of a Data Practice - Adrian Mackenzie 2017 PDF | DJVU The MIT Press BOOKS PROGRAMMING
ECO~14 kg CO²

1 TON

Views
98637

Telegram
 
Machine Learners Archaeology of a Data Practice
Author: Adrian Mackenzie
Year: 2017
Pages: 272
Format: PDF | DJVU
File size: 10.19 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Before Machine Learning, Volume 2 - Calculus for A.I. The fundamental mathematics for Data Science and Artificial Intelligence
Scaling Python with Dask From Data Science to Machine Learning (Sixth Early Release)
No-Code Data Science Mastering Advanced Analytics, Machine Learning, and Artificial Intelligence
Data Analytics: Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life
Advanced Data Analytics with AWS Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources
Advanced Data Analytics with AWS Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources
Data Analytics Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life
Graph-Powered Analytics and Machine Learning with TigerGraph: Driving Business Outcomes with Connected Data
Detecting Regime Change in Computational Finance Data Science, Machine Learning and Algorithmic Trading
Google BigQuery The Definitive Guide Data Warehousing, Analytics, and Machine Learning at Scale, First Edition
Architecting Data and Machine Learning Platforms Enable Analytics and AI-Driven Innovation in the Cloud (Final)
Before Machine Learning Volume 1 - Linear Algebra for A.I. The fundamental mathematics for Data Science and Artificial Inteligence
Before Machine Learning Volume 1 - Linear Algebra for A.I: The fundamental mathematics for Data Science and Artificial Inteligence.
Applied Machine Learning for Smart Data Analysis (Computational Intelligence in Engineering Problem Solving)
Architecting Data and Machine Learning Platforms Enable Analytics and AI-Driven Innovation in the Cloud (Final)
Machine Learning Interview Guide Job-oriented questions and answers for data scientists and engineers
Machine Learning Cookbook with Python Create ML and Data Analytics Projects Using Some Amazing Open Datasets
Artificial Intelligence and Machine Learning for Business A No-Nonsense Guide to Data Driven Technologies, Third Edition
Applied Text Analysis with Python Enabling Language Aware Data Products with Machine Learning
Before Machine Learning Volume 1 - Linear Algebra for A.I. The fundamental mathematics for Data Science and Artificial Inteligence
Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources (English Edition)
Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing, Data Analysis, and Cyber Security
Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing, Data Analysis, and Cyber Security
Power BI Machine Learning and OpenAI: Explore data through business intelligence, predictive analytics, and text generation
Machine Learning for Civil and Environmental Engineers A Practical Approach to Data-driven Analysis, Explainability, and Causality
Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python
Machine Learning for Business How to Build Artificial Intelligence through Concepts of Statistics, Algorithms, Analysis, and Data Mining
Introduction to Data Governance for Machine Learning Systems Fundamental Principles, Critical Practices, and Future Trends
Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Feature Engineering for Modern Machine Learning with Scikit-Learn Advanced Data Science and Practical Applications
Machine Learning for Civil and Environmental Engineers: A Practical Approach to Data-Driven Analysis, Explainability, and Causality
The Data Revolution Big Data, Open Data, Data Infrastructures and Their Consequences
Machine Learning Design Patterns Solutions to Common Challenges in Data Preparation, Model Building, and MLOps, First Edition
Python Programming: An Introductory Guide for Accounting and Finance (Machine Learning, Financial Analysis, Data Visualization, Automation and More)
Modern Data Architectures with Python: A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python
Data Modeling Made Simple with Embarcadero ER/Studio Data Architect Adapting to Agile Data Modeling in a Big Data World
Graph-Powered Analytics and Machine Learning with TigerGraph Driving Business Outcomes with Connected Data (10th Early Release)
The Python Bible 7 in 1 Volumes One To Seven (Beginner, Intermediate, Data Science, Machine Learning, Finance, Neural Networks, Computer Vision)
Graph-Powered Analytics and Machine Learning with TigerGraph Driving Business Outcomes with Connected Data (9th Early Release)
Python Programmieren 7 in 1 Der schnelle Einstieg (Grundlagen, Machine Learning, Neuronale Netze, Data Science, Computer Vision, Finanzen)