Model-Based Clustering and Classification for #DataScience, with Applications in R: http://
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DATA
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Model-Based Clustering and Classification for Data Science in R
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Python for Geospatial Data Analysis and Location Intelligence
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#Python for #Geospatial Data Analysis and Location Intelligence: http://
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Updated Third Edition: Bayesian Analysis with Python Practical Guide
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UPDATED Third Edition "Bayesian Analysis with #Python — Practical Guide to Probabilistic Modeling": http://
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New Python Data Analysis Book with Hands-on Pandas Challenges
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Check out this great new book >> 50 Days of Data Analysis with #Python — The Ultimate Challenges Book for Beginners, with Hands-on Challenges using Pandas, NumPy, Matplotlib, Sklearn and Seaborn: http://
amzn.to/3uQfgrR by @RealBenjizo —————
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Extended PowerBI Guide with Python and R Analytics
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Updated (2nd edition) 814-page book from @PacktDataML at http://
amzn.to/49xRKOk "Extending #PowerBI with #Python and R — Advanced analysis using the power of analytical languages" #DataScience #Analytics #BI #Rstats #CDO (comes with link to free PDF eBook) -

Python Finance Cookbook: 80+ Recipes for Financial Data Analysis
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#Python for #Finance Cookbook with 80+ powerful recipes for financial data analysis: http://
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Data Cleaning and Exploration with Machine Learning Guide
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Data Cleaning and Exploration with Machine Learning: http://
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Exploratory Data Analysis with Python: 50 EDA Recipes
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Exploratory Data Analysis with #Python Cookbook — Over EDA 50 recipes to analyze, visualize, and extract insights from structured & unstructured data: http://
amzn.to/3S7Hjuk by @AyoOluleye v/ @PacktDataML ————
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Machine Learning and Generative AI for Marketing with Python
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#MachineLearning and #GenerativeAI for Marketing using #Python — http://
amzn.to/4dNES9Z via @PacktDataML Key Features: Enhance customer engagement and personalization through predictive analytics and advanced segmentation techniques Combine Python programming with the -

Data Quality Over Quantity in Robotics Production Systems
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Thx John for this excellent summary. Data quality vs data quantity is a crucial issue; that’s why data flywheels like @AmbiRobotics can be effective: they collect real production data from real packages in real logistics environments.