Machine Learning & AI
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A Unique Method for Machine Learning Interpretability: Game Theory & Shapley Values!

Overview Learn how to use Shapley values in game theory for machine learning interpretability It’s a unique and different perspective to interpret black-box machine ...
The post A Unique Method for Machine Learning Interpretability: Game Theory & Shapley Values! appeared first on Analytics Vidhya.

https://www.analyticsvidhya.com/blog/2019/11/shapley-value-machine-learning-interpretability-game-theory/
Top Stories, Nov 18-24: How to Speed up Pandas by 4x with one line of code; Python, Selenium & Google for Geocoding Automation: Free and Paid

Also: Automated Machine Learning Project Implementation Complexities; Text Encoding: A Review; The Notebook Anti-Pattern; Data Science for Managers: Programming Languages; 10 Free Must-read Books on AI

https://www.kdnuggets.com/2019/11/top-news-week-1118-1124.html
Top 8 Data Science Use Cases in Marketing

In this article, we want to highlight some key data science use cases in marketing. Let us concentrate on several instances that present particular interest and managed to prove their efficiency in the course of time.

https://www.kdnuggets.com/2019/11/top-8-data-science-use-cases-marketing.html
Would you buy insights from this guy? (How to assess and manage a Data Science vendor)

With all the hype from data science vendors selling "actionable insights" to boost your company's bottom line, selecting your analytics partner should proceed through the same, careful process as any traditional business endeavor. Follow these questions and best practices to ensure you manage accordingly.

https://www.kdnuggets.com/2019/11/assess-data-science-vendor.html
Probability Learning: Naive Bayes

This post will describe various simplifications of Bayes' Theorem, that make it more practical and applicable to real world problems: these simplifications are known by the name of Naive Bayes. Also, to clarify everything we will see a very illustrative example of how Naive Bayes can be applied for classification.

https://www.kdnuggets.com/2019/11/probability-learning-naive-bayes.html
Machine Learning 101: The What, Why, and How of Weighting

Weighting is a technique for improving models. In this article, learn more about what weighting is, why you should (and shouldn’t) use it, and how to choose optimal weights to minimize business costs.

https://www.kdnuggets.com/2019/11/machine-learning-what-why-how-weighting.html
AXA, State Auto and Hippo on how to fuse innovative tech to your company

Join this live webinar: Fast, Agile, Service-Driven Insurance: Fuse Innovative Tech to Your Company DNA - AI, Chatbots, Automation and More, Dec 11 at 10:00am EST, to get actionable insight to develop your strategy.

https://www.kdnuggets.com/2019/11/insurancenexus-innovative-tech-webinar.html
What is the Chi-Square Test and How Does it Work? An Intuitive Explanation with R Code

Overview What is the chi-square test? How does it work? Learn about the different types of Chi-Square tests and where and when you should ...
The post What is the Chi-Square Test and How Does it Work? An Intuitive Explanation with R Code appeared first on Analytics Vidhya.

https://www.analyticsvidhya.com/blog/2019/11/what-is-chi-square-test-how-it-works/
KDnuggets™ News 19:n45, Nov 27: Interpretable vs black box models; Advice for New and Junior Data Scientists

This week: Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead; Advice for New and Junior Data Scientists; Python Tuples and Tuple Methods; Can Neural Networks Develop Attention? Google Thinks they Can; Three Methods of Data Pre-Processing for Text Classification

https://www.kdnuggets.com/2019/n45.html
Task-based effectiveness of basic visualizations

This is a summary of a recent paper on an age-old topic: what visualisation should I use? No prizes for guessing “it depends!” Is this the paper to finally settle the age-old debate surrounding pie-charts??

https://www.kdnuggets.com/2019/11/task-based-effectiveness-basic-visualizations.html
Spark NLP 101: LightPipeline

A Pipeline is specified as a sequence of stages, and each stage is either a Transformer or an Estimator. These stages are run in order, and the input DataFrame is transformed as it passes through each stage. Now let’s see how this can be done in Spark NLP using Annotators and Transformers.

https://www.kdnuggets.com/2019/11/spark-nlp-101-lightpipeline.html
The Future of Careers in Data Science & Analysis

As the fields of data science and analysis continue to expand, the next crop of bright minds is always needed. Learn more about the nuances of these jobs and find where you can fit in for a rewarding and interesting career.

https://www.kdnuggets.com/2019/11/future-careers-data-science-analysis.html
Top KDnuggets tweets, Nov 20-26: How to Speed up Pandas by 4x with one line of code

Also: Deep Learning for Image Classification with Less Data; How to Speed up Pandas by 4x with one line of code; 25 Useful #Python Snippets to Help in Your Day-to-Day Work; Automated Machine Learning Project Implementation Complexities

https://www.kdnuggets.com/2019/11/top-tweets-nov20-26.html
DSAT – First Ever Adaptive Learning Platform for Data Science Professionals

“Every once in a while, a revolutionary product comes along that changes everything.” – Steve Jobs We are thrilled to announce the launch of ...
The post DSAT – First Ever Adaptive Learning Platform for Data Science Professionals appeared first on Analytics Vidhya.

https://www.analyticsvidhya.com/blog/2019/11/dsat-adaptive-learning-platform-data-science/
Open Source Projects by Google, Uber and Facebook for Data Science and AI

Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.

https://www.kdnuggets.com/2019/11/open-source-projects-google-uber-facebook-data-science-ai.html
Lit BERT: NLP Transfer Learning In 3 Steps

PyTorch Lightning is a lightweight framework which allows anyone using PyTorch to scale deep learning code easily while making it reproducible. In this tutorial we’ll use Huggingface's implementation of BERT to do a finetuning task in Lightning.

https://www.kdnuggets.com/2019/11/lit-bert-nlp-transfer-learning-3-steps.html