Introduction to various #ReinforcementLearning #Algorithms: http://
bit.ly/2UPHbSj
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See this foundational book (2nd edition): http://
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@kirkdborne
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Introduction to Reinforcement Learning Algorithms and Foundational Resources
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Deep Reinforcement Learning Hands-On Guide: Q-learning to RLHF
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Deep #ReinforcementLearning Hands-On — Practical easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF: http://
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𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Learn with -
Comprehensive Python Machine Learning Guide: 772-Page Third Edition Book
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Learn Python for #MachineLearning comprehensively in this massive 772-page book:
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Machine Learning for Time Series Forecasting and Anomaly Detection
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#MachineLearning for #TimeSeries with #Python — Forecast trends, Predict the future, Detect anomalies with state-of-the-art #ML methods: http://
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AIoT: Artificial Intelligence of Things and Machine Learning Techniques
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The Artificial Intelligence of Things #AIoT: https://
techtarget.com/iotagenda/defi
nition/Artificial-Intelligence-of-Things-AIoT
… AIoT book v/ @PacktDataML → Hands-On #AI for #IoT — Expert #MachineLearning & #DeepLearning techniques for developing smarter IoT systems [2nd Ed.]: http://
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Streamlit: Transform Data Scripts into Interactive Web Apps Quickly
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Streamlit turns your data scripts into shareable web apps in minutes: http://
streamlit.io
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"Streamlit for #DataScience" = Step-by-step guide to building interactive data apps in #Python — http://
amzn.to/45bY8IZ v/ @PacktDataML ———
#DataScientist #AI #ML #DataViz #Analytics -
Handling Imbalanced Data in Machine Learning and Deep Learning
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Tutorials on Imbalanced Data: https://
analyticsvidhya.com/blog/2021/06/5
-techniques-to-handle-imbalanced-data-for-a-classification-problem/
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#MachineLearning & #DeepLearning Techniques for Handling Imbalanced Data: http://
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Explore the metrics used when classes are imbalanced.
Use imbalanced data in your machine learning -
Machine Learning Pipelines and Microservices Architecture for Production
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Data in, intelligence out: https://
infoworld.com/article/225288
9/data-in-intelligence-out-machine-learning-pipelines-demystified.html
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Machine Learning in Microservices — Productionizing microservices architecture for #MachineLearning solutions: http://
amzn.to/4iIptKB v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
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Building AI Agents with LLMs RAG and Knowledge Graphs
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"Building AI Agents with LLMs, RAG, and Knowledge Graphs — A practical guide to autonomous and modern AI agents" See it at http://
amzn.to/4622k2h via @PacktDataML -
Python Tools for Scientists: Anaconda, JupyterLab, Scientific Libraries
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#Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python's Scientific Libraries →→ Get it at http://
amzn.to/3WrBmZf [744-page book from @NoStarch Press]
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