2019 News
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KDnuggets News issues for 2019
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19:n49: What is a Data Scientist Worth? New Explainable AI from Google - Dec 27, 2019.
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19:n48: Build Pipelines with Pandas Using pdpipe; AI, Analytics, ML, DS, Technology Main Developments, Key Trends; Poll on AutoML - Dec 18, 2019.
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19:n47: 10 Free Top Notch Machine Learning Courses; AI, Analytics, ML, DS Main Developments and Key Trends - Dec 11, 2019.
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19:n46: The Future of Data Science Careers; Which Data Visualization Should I Use? - Dec 4, 2019.
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19:n45: Interpretable vs black box models; Advice for New and Junior Data Scientists - Nov 27, 2019.
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19:n44: How I Got Better at Machine Learning; Tips for a cost-effective ML project - Nov 20, 2019.
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19:n43: Dynamic Reports in Python and R; Creating NLP Vocabularies; What is Data Science? - Nov 13, 2019.
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19:n42: 5 Statistical Traps Data Scientists Should Avoid; 10 Free Must-Read Books on AI - Nov 6, 2019.
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19:n41: Feature Selection: Beyond feature importance?; Time Series Analysis Using KNIME and Spark - Oct 30, 2019.
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19:n40: How to Become a (Good) Data Scientist; Writing Your First Neural Net in 30 Lines with Keras - Oct 23, 2019.
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19:n39: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI - Oct 16, 2019.
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19:n38: The Last SQL Guide for Data Analysis; 4 Quadrants of Data Science Skills and 7 steps for Viral Data Visualization - Oct 9, 2019.
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19:n37: The Future of Analytics & Data Science! Starting NLP with spaCy & Python - Oct 2, 2019.
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19:n36: The Hidden Risk of AI and Big Data; The 5 Sampling Algorithms every Data Scientist needs to know - Sep 25, 2019.
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19:n35: Which Data Science Skills are core and which are hot/emerging ones?; There is No Free Lunch in Data Science Features - Sep 18, 2019.
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19:n34: I wasn’t getting hired as a Data Scientist. So I sought data on who is - Sep 11, 2019.
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19:n33: Data Science Skills Poll; Object-oriented Programming for Data Scientists - Sep 4, 2019.
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19:n32: Handy SQL Features for Data Scientists; Nothing but NumPy: Creating Neural Networks with Computational Graphs - Aug 28, 2019.
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19:n31: Become a Marketable Data Scientist; Data Science Command Line Basics; Chatbots with Keras - Aug 21, 2019.
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19:n30: Know Your Neighbor: Machine Learning on Graphs; 12 NLP Researchers, Practitioners You Should Follow - Aug 14, 2019.
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19:n29: What 70% of Data Science Learners Do Wrong; Pytorch Cheat Sheet for Beginners - Aug 7, 2019.
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19:n28: Top 13 Skills To Become a Rockstar Data Scientist; Best Podcasts on AI, Analytics, Data Science - Jul 31, 2019.
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19:n27: Bayesian deep learning and near-term quantum computers; DeepMind’s CASP13 Protein Folding Upset Summary - Jul 24, 2019.
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19:n26: The Death of Big Data and the Emergence of Multi-Cloud; Top 10 Data Science Leaders You Should Follow - Jul 17, 2019.
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19:n25: 5 Probability Distributions for Data Scientists; What the Machine Learning Engineer Job is Really Like - Jul 10, 2019.
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19:n24: Understand Cloud Services; Pandas Tips & Tricks; Master Data Preparation w/ Python - Jun 26, 2019.
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19:n23: Useful Stats for Data Scientists; Python, TensorFlow & R Winners in Latest Job Report - Jun 19, 2019.
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19:n22: The Modern Open-Source Data Science/Machine Learning Ecosystem; Simplifying the Data Visualisation Process in Python - Jun 12, 2019.
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19:n21: Transitioning your Career to Data Science; 11 top Data Science, Machine Learning platforms; 7 Steps to Mastering Intermediate ML w. Python - Jun 5, 2019.
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19:n20: 7 Steps to Mastering SQL for Data Science; How to build Math Programming Skills - May 22, 2019.
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19:n19: Data Scientist – Best Job of the Year!; How (not) to use Machine Learning for time series forecasting - May 15, 2019.
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19:n18: What Data Science/Machine Learning software you used – KDnuggets Poll; The Third Wave Data Scientist - May 8, 2019.
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19:n17: The most desired skill in data science; Seeking KDnuggets Editors, work remotely - May 1, 2019.
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19:n16: Data Visualization in Python with Matplotlib & Seaborn; Getting Into Data Science: The Ultimate Q&A - Apr 24, 2019.
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19:n15: Time Series Forecasting with Neural Nets and LSTM; Why Data Scientists Need To Work In Groups - Apr 17, 2019.
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19:n14: Which Data Science/ML methods and algorithms you used? Predict Age and Gender Using Neural Nets - Apr 10, 2019.
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19:n13: Top 10 Data Scientist Coding Mistakes; Explaining Random Forest®; Which Face is Real? - Apr 3, 2019.
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19:n12: My Best Tips for Agile Data Science Research; R vs Python for Data Visualization - Mar 27, 2019.
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19:n11: Another 10 Free Must-Read Books for Data Science; 19 Inspiring Women in AI, Big Data, Machine Learning - Mar 20, 2019.
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19:n10: What no one will tell you about data science job applications; The rise of ML Engineering - Mar 6, 2019.
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19:n09: Where did you apply Analytics, Machine Learning, and Data Science in 2018?; Python Data Science for Beginners - Feb 27, 2019.
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19:n08: The Gold Standard of Python Machine Learning; The Analytics Engineer – new role in the data team - Feb 20, 2019.
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19:n07: The Best and Worst Data Visualizations of 2018; Gartner 2019 Magic Quadrant for Data Science Platforms - Feb 13, 2019.
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19:n06: Data Scientists: Why are they so expensive to hire? An Essential Data Science Venn Diagram - Feb 6, 2019.
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19:n05: Your AI skills are worth less than you think; 7 Steps to Mastering Basic Machine Learning - Jan 30, 2019.
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19:n04: Top 7 Python Libraries for Data Science and AI; Ontology and Data Science - Jan 23, 2019.
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19:n03: Top 10 Books on NLP and Text Analysis; End To End Guide For Machine Learning Projects - Jan 16, 2019.
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19:n02: The cold start problem: how to build your machine learning portfolio; 5 Best Data Visualization Libraries - Jan 9, 2019.
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19:n01: The Essence of Machine Learning; A Guide to Decision Trees for Machine Learning and Data Science - Jan 3, 2019.
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