Data Science for Managers: Programming Languages

In this article, we are going to talk about popular languages for Data Science and briefly describe each of them.

https://www.kdnuggets.com/2019/11/data-science-managers-programming-languages.html

The Math Behind Bayes

This post will be dedicated to explaining the maths behind Bayes Theorem, when its application makes sense, and its differences with Maximum Likelihood.

https://www.kdnuggets.com/2019/11/math-behind-bayes.html

Reproducibility, Replicability, and Data Science

As cornerstones of scientific processes, reproducibility and replicability ensure results can be verified and trusted. These two concepts are also crucial in data science, and as a data scientist, you must follow the same rigor and standards in your projects.

https://www.kdnuggets.com/2019/11/reproducibility-replicability-data-science.html

SkillsUP Lab Encourages Employers to Invest in Lifelong Learning

Data fluency and continuous learning are desperately needed—especially in tight job markets like The Netherlands.

https://www.datacamp.com/community/blog/skills-up-lab

How to apply machine learning and deep learning methods to audio analysis

Find out how data scientists and AI practitioners can use a machine learning experimentation platform like Comet.ml to apply machine learning and deep learning to methods in the domain of audio analysis.

https://www.kdnuggets.com/2019/11/comet-machine-learning-deep-learning-audio.html

Why write for KDnuggets? Calling for original blogs and new authors

KDnuggets is calling for original blogs and contributions from new authors on AI, Data Science, Machine Learning, and related topics. The authors of most popular such blogs in December will be profiled in KDnuggets.

https://www.kdnuggets.com/2019/11/write-for-kdnuggets.html

A Comprehensive Guide to Attention Mechanism in Deep Learning for Everyone

 Overview The attention mechanism has changed the way we work with deep learning algorithms Fields like Natural Language Processing (NLP) and even Computer Vision ...
The post A Comprehensive Guide to Attention Mechanism in Deep Learning for Everyone appeared first on Analytics Vidhya.

https://www.analyticsvidhya.com/blog/2019/11/comprehensive-guide-attention-mechanism-deep-learning/

KDnuggets™ News 19:n44, Nov 20: How I Got Better at Machine Learning; Tips for a cost-effective ML project

Read tips and tricks that helped one Data Scientist to get better at Machine Learning; Learn how to make ML project cost-effective; Consider submitting a blog to KDnuggets - you can be profiled here; and study how to manipulate Python lists.

https://www.kdnuggets.com/2019/n44.html

Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

The two main takeaways from this paper: firstly, a sharpening of my understanding of the difference between explainability and interpretability, and why the former may be problematic; and secondly some great pointers to techniques for creating truly interpretable models.

https://www.kdnuggets.com/2019/11/stop-explaining-black-box-models.html

Deep Learning for Image Classification with Less Data

In this blog I will be demonstrating how deep learning can be applied even if we don’t have enough data.

https://www.kdnuggets.com/2019/11/deep-learning-image-classification-less-data.html

Pro Tips: How to deal with Class Imbalance and Missing Labels

Your spectacularly-performing machine learning model could be subject to the common culprits of class imbalance and missing labels. Learn how to handle these challenges with techniques that remain open areas of new research for addressing real-world machine learning problems.

https://www.kdnuggets.com/2019/11/tips-class-imbalance-missing-labels.html

The Semiconductor Imperative for Driving Meaningful Innovation

The fundamental fact is that more information than ever will need to be analyzed on millions of devices. And that’s where 5G will make accessing data dramatically faster and more efficient. At Samsung, we’re excited about what 5G can truly enable and to be a central player in the new 5G world.

https://www.kdnuggets.com/2019/11/samsung-semiconductor-innovation.html

Python Tuples and Tuple Methods

Brush up on your Python basics with this post on creating, using, and manipulating tuples.

https://www.kdnuggets.com/2019/11/python-tuples-methods.html

The Notebook Anti-Pattern

This article aims to explain why this drive towards the use of notebooks in production is an anti pattern, giving some suggestions along the way.

https://www.kdnuggets.com/2019/11/notebook-anti-pattern.html

Top KDnuggets tweets, Nov 13-19: A whole lot of Data Science Cheatsheets

Also: Bring the scientific rigor of reproducibility to your Data Science projects; Neutrinos Lead to Unexpected Discovery in Basic Math ; The media gets really excited about AI. Maybe a bit too excited

https://www.kdnuggets.com/2019/11/top-tweets-nov13-19.html

Neural Networks 201: All About Autoencoders

Autoencoders can be a very powerful tool for leveraging unlabeled data to solve a variety of problem, such as learning a "feature extractor" that helps build powerful classifiers, finding anomalies, or doing a Missing Value Imputation.

https://www.kdnuggets.com/2019/11/all-about-autoencoders.html

Geocoding Automation: Free and Paid with Python, Selenium and Google

This tutorial will take you through two options that have automated the geocoding process for the user using Python, Selenium and Google Geocoding API.

https://www.kdnuggets.com/2019/11/automate-geocoding-free-paid-python-selenium-google.html

Three Methods of Data Pre-Processing for Text Classification

This blog shows how text data representations can be used to build a classifier to predict a developer’s deep learning framework of choice based on the code that they wrote, via examples of TensorFlow and PyTorch projects.

https://www.kdnuggets.com/2019/11/ibm-data-preprocessing-text-classification.html

Text Encoding: A Review

We will focus here exactly on that part of the analysis that transforms words into numbers and texts into number vectors: text encoding.

https://www.kdnuggets.com/2019/11/text-encoding-review.html

Implementation Complexities of Automated Machine Learning Projects

To demonstrate the implementation complexity differences along the AutoML highway, let's have a look at how 3 specific software projects approach the implementation of just such an AutoML "solution," namely Keras Tuner, AutoKeras, and automl-gs.

https://www.kdnuggets.com/2019/11/automl-implementation-complexities.html

Exception and Error Handling in Python

Error handling increases the robustness of your code, which guards against potential failures that would cause your program to exit in an uncontrolled fashion.

https://www.datacamp.com/community/tutorials/exception-handling-python