Linear Algebra and Optimization for Machine Learning [516-page textbook]: http://
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This textbook is organized around its 2 main themes:
[Amazon Summary] 1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with
@kirkdborne
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Textbook Links Linear Algebra and Optimization to Machine Learning
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Python Forecasting Guide Covers Global Models, PyTorch and Pandas
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Modern Time Series Forecasting with Python — Industry-ready Machine Learning and Deep Learning time series analysis with PyTorch and PANDAS: http://
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Machine Learning Guide Builds Trading Signals From Alternative Data
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Machine Learning for Algorithmic Trading — Predictive models to extract signals from market and alternative data for systematic trading strategies with Python… and for *other* Time Series prediction applications Explore http://
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A PyTorch Deep Learning Toolkit for Real-World Time Series Forecasting
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From @PacktPublishing @PacktDataML … "Time Series with PyTorch: Modern Deep Learning Toolkit for Real-World Forecasting Challenges", available at http://
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AI Engineering Guide Covers Building Applications With Foundation Models
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AI Engineering — Building Applications with Foundation Models: http://
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Understand what AI engineering is and how it differs from traditional machine learning engineering Learn the -
Fifty Machine Learning Projects Explore Transformer Mechanisms
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50 ML projects to understand LLMs — Investigate transformer mechanisms through data analysis, visualization, & experimentation: http://
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Thirty Agent Projects Cover Reliable Production Architectures
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30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
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What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and -
Guide Combines Neo4j Knowledge Graphs and LLMs for Intelligent Search
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Available at http://
amzn.to/4l9lLKO This LLM book is for database developers and data scientists who want to leverage knowledge graphs with Neo4j and its vector search capabilities to build intelligent search and recommendation systems. Working knowledge of Python and Java is -
Guide Takes Machine Learning Applications From Idea to Production
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Learn both how to build and how to ship ML models into production >> "Building Machine Learning Powered Applications — Going from Idea to Product": http://
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Machine Learning Engineer Cookbook Covers Deep Learning and Generative AI
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AI Mastery >> The Complete Machine Learning Engineer Cookbook for Everyone — Become an AI Developer with Python: http://
amzn.to/3XZTzQS Complete 5-part Learning Path:
1 – Build Your Foundation
2 – Assemble Your ML Toolkit
3 – Discover Deep Learning & Generative AI
4 – Master