Category: Artificial Intelligence

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Artificial Intelligence Education Innovation Reading

Latest Read: Deep Reinforcement Learning


Deep Reinforcement Learning in Action by Alexander Zai.

Deep Reinforcement Learning in Action by Alexander Zai

Alex holds a BS in Chemical Engineering and Biochemistry from the University of California, Los Angeles (UCLA)., where he graduated in 2014. He co-founded Codesmith and led its Data Science and Machine Learning research group. He has also been involved in advancing TensorFlow.js, focusing on enabling browser-level deep learning and computer vision applications. Today Alex is a Machine Learning Engineer at Amazon AI.

Reinforcement Learning (RL) is certainly one of the most intellectually demanding subfields of Machine Learning. Alex takes a very pragmatic approach by writing this book for the developer who wants to understand the “why” engaging with the “how.” He is utilizing PyTorch as the vehicle, providing a clean, Python interface to very complex algorithms.

Humans learn best from feedback. We are encouraged to take actions that lead to positive results. This reinforcement is applied to computer programs allowing them to solve more complex problems. Deep Reinforcement Learning in Action teaches readers how to program AI agents that adapt and improve based on direct feedback from their environment.

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Artificial Intelligence Education Innovation Reading

Latest Read: Regular Expression Puzzles

Regular Expression Puzzles and AI Coding Assistants: 24 puzzles solved by the author, with and without assistance from Copilot, ChatGPT and more by David Mertz.

Regular Expression Puzzles and AI Coding Assistants by David Mertz

David holds a PhD in Philosophy from the University of Massachusetts Amherst. He is a leading figure in the Python and data science communities. He is the former Director of the Python Software Foundation.

This book revolves around 24 puzzles that range from basic string manipulation to very complex regular expression (regex) tasks. David is providing his expert solutions in Python. And with the explosion of AI Chatbots, he then prompts GitHub Copilot and ChatGPT to solve the same problems.

These lessons provide insights to enhance your productivity by writing regular expressions. David also offers AI best practices, showing how smart prompts return better results. By the end, you’ll be a master at solving your own Regex puzzles, whether you use AI or not.

Rather than being a traditional, dry academic textbook, he shows the puzzles in a “man vs. machine” competition. This is perhaps a modern AI version of the song Big John in American folklore..

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Artificial Intelligence Education Innovation Reading

Latest Read: Creepy Analytics

Creepy Analytics: Avoid Crossing the Line and Establish Ethical HR Analytics for Smarter Workforce Decisions by Salvatore V. Falletta.

Creepy Analytics: Avoid Crossing the Line and Establish Ethical HR Analytics for Smarter Workforce Decisions by Salvatore V. Falletta

Salvatore holds a EdD in Human Resource Development from North Carolina State University and a Master of Public Administration with a specialty in HR and Organization Development from Indiana State University. He previously served as Vice President and Chief Human Resources Officer for Atmel Corporation and held leadership HR roles at Intel, SAP, and Sun Microsystems. Today Salvatore is a Professor of the Practice at Vanderbilt University.

Salvatore is revealing while AI can certainly augment an HR Recruiter’s efficiency, it simply cannot operate in a vacuum. Similar to many authors, a Human In The Loop (HITL) is absolutely mandatory to prevent a datafication of people from turning into surveillance.

Similarly, his golden rule is that AI should never make a final workforce decision alone. This is understood as ‘Augmentation, Not Replacement’ AI should be used to scan thousands of resumes, but human recruiters must provide the final judgment.

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Artificial Intelligence Education Reading

Latest Read: The Predictive Edge

The Predictive Edge: Outsmart the Market using Generative AI and ChatGPT in Financial Forecasting by Alejandro Lopez-Lira.

The Predictive Edge: Outsmart the Market using Generative AI and ChatGPT in Financial Forecasting by Alejandro Lopez-Lira

Alejandro holds a MA and PhD in Finance from the University of Pennsylvania.Today he is an Assistant Professor of Finance at the University of Florida.

In the AI-accelerated landscape of financial technology, he is taking a view that legacy quantitative methods face diminishing returns. So here, a new “predictive edge” in Large Language Models has arrived. Perhaps a mix of theory and practice for integrating AI into your investment strategies.

Financial forecasting traditionally relied on structured data: price charts, earnings ratios, and trading volumes. Alejandro is now showing the market’s greatest inefficiency resides in unstructured data. Every day a large volume of news, earnings call transcripts, and regulatory filings have broken those legacy forecasting models. Enter ChatGPT and LLMs which hold the ability to process and perform sentiment analysis at a scale previously impossible.

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Artificial Intelligence Education Reading

Latest Read: Generative AI in Action

Generative AI in Action by Amit Bahree.

Generative AI in Action by Amit Bahree

Amit holds an MSc in Software Engineering from the University of Oxford and a BSc in Computer Science from the University of Pune. He previously served as Chief Technology Innovation Officer at Avanade. He is also a co-author of Pro WCF: Practical Microsoft SOA Implementation. Today he serves as a Principal Group Product Manager for the Azure AI engineering team at Microsoft.

Generative AI in Action certainly provides a high-level roadmap for integrating Large Language Models into organizational enterprise environments. He is linking the “magic” of AI’s hype cycle with the demands of production architectures across diverse organizations.

This is not a “how to use ChatGPT” guide for non-technical users. This is however a good book for experienced software developers, architects, and data scientists who are new to AI. It explains the core concepts from scratch and provides a learning path sans PhD in mathematics. So, generating quick prompts from poetry to dinner recipes, the demands of building enterprise, scalable AI services is rather challenging.

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