Stop training more models, start deploying them
We are hardly living up to the promises of AI in healthcare. It’s not because of our training, it’s because of our deployment.
on Jun 30, 2020 in Deployment, Modeling, Training
Software engineering fundamentals for Data Scientists
As a data scientist writing code for your models, it's quite possible that your work will make its way into a production environment to be used by the masses. But, writing code that is deployed as software is much different than writing code for exploratory data analysis. Learn about the key approaches for making your code production-ready that will save you time and future headaches.
on Jun 30, 2020 in Advice, Best Practices, Data Science, Programming, Software Engineering
The Unreasonable Progress of Deep Neural Networks in Natural Language Processing (NLP)
Natural language processing has made incredible advances through advanced techniques in deep learning. Learn about these powerful models, and find how close (or far away) these approaches are to human-level understanding.
on Jun 29, 2020 in Deep Learning, LSTM, NLP, Transfer Learning, Transformer, Trends
An Introduction to Statistical Learning: The Free eBook
This week's free eBook is a classic of data science, An Introduction to Statistical Learning, with Applications in R. If interested in picking up elementary statistical learning concepts, and learning how to implement them in R, this book is for you.
on Jun 29, 2020 in Free ebook, R, Robert Tibshirani, Statistical Learning, Trevor Hastie
Practical Markov Chain Monte Carlo
This is a slightly more intricate example of MCMC, compared to many with a fairly simple model, a single predictor (maybe two), and not much else, which highlights a couple of issues and tricks worth noting for a handwritten implementation.
on Jun 26, 2020 in Bayesian, Markov Chains, Monte Carlo, R
Data Science Tools Popularity, animated
Watch the evolution of the top 10 most popular data science tools based on KDnuggets software polls from 2000 to 2019.
on Jun 25, 2020 in About KDnuggets, Data Science Platform, Poll, Python, R
Lynx Analytics is open-sourcing LynxKite, its Complete Graph Data Science Platform
Check out this article for a brief summary on what LynxKite is, where it is coming from and how it can help with your data science projects.
on Jun 25, 2020 in Data Science Platform, Graph Analytics, Open Source
 Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron
DeepMind’s research shows how to understand the role of individual neurons in a neural network.
on Jun 25, 2020 in Deep Learning, DeepMind, Learning, Neural Networks
Machine Learning Engineer vs Data Scientist (Is Data Science Over?)
What has been happening to the definition of Data Scientist over the past 5 years? Does it still exist or has it morphed into a new version of its old self? Learn more about the recent trends in job descriptions and salaries for data scientists, ML engineers, and others to best understand the best fit for your career trajectory and interests.
on Jun 25, 2020 in Career, Data Scientist, Machine Learning Engineer
Free Economics & Finance Courses for Data Scientists
Here is a selection of courses for those interested in diversifying their domain knowledge into the related realms of economics and finance, with the goal of being able to apply your data science skills to these domains.
on Jun 25, 2020 in Courses, Economics, Finance, MOOC
Five Lines of Code
If you want to learn simple and practical rules for coding and refactoring, "Five Lines of Code" from Manning is the guide for you, teaching you concrete principles for refactoring. Save 40% with code nlfive40 until July 24.
on Jun 24, 2020 in Best Practices, Book, Manning, Programming
Build a Branded Web Based GIS Application Using R, Leaflet and Flexdashboard
By using R, Flexdashboard and Leaflet, we can build a customized and branded web application to showcase location based data interactively across the organization. Instead of crowding the application with many widgets, we use menu tabs and pages to separate the interactive aspects.
on Jun 24, 2020 in Data Scientist, Data Visualization, Geospatial, GIS, Leaflet, R, Rstudio
Time Complexity: How to measure the efficiency of algorithms
When we consider the complexity of an algorithm, we shouldn’t really care about the exact number of operations that are performed; instead, we should care about how the number of operations relates to the problem size.
on Jun 24, 2020 in Algorithms, Complexity, Programming
Tools to Spot Deepfakes and AI-Generated Text
The technologies that generate deepfake content is at the forefront of manipulating humans. While the research developing these algorithms is fascinating and will lead to powerful tools that enhance the way people create and work, in the wrong hands, these same tools drive misinformation at a scale we can't yet imagine. Stopping these bad actors using awesome tools is in your hands.
on Jun 23, 2020 in AI, Deep Learning, Deepfakes, Natural Language Generation
Bias in AI: A Primer
Those interested in studying AI bias, but who lack a starting point, would do well to check out this introductory set of slides and the accompanying talk on the subject from Google researcher Margaret Mitchell.
on Jun 23, 2020 in AI, Bias, Computer Vision, NLP
Machine Learning in Dask
In this piece, we’ll see how we can use Dask to work with large datasets on our local machines.
on Jun 22, 2020 in Dask, Machine Learning, Pandas, Python
 4 Free Math Courses to do and Level up your Data Science Skills
Just as there is no Data Science without data, there's no science in data without mathematics. Strengthening your foundational skills in math will level you up as a data scientist that will enable you to perform with greater expertise.
on Jun 22, 2020 in Bayesian, Coursera, edX, Inference, Linear Algebra, Mathematics, Online Education, Principal component analysis, Probability, Python, Statistics
How to Deal with Missing Values in Your Dataset
In this article, we are going to talk about how to identify and treat the missing values in the data step by step.
on Jun 22, 2020 in Data Preparation, Data Preprocessing, Missing Values, Python
Graph Machine Learning in Genomic Prediction
This work explores how genetic relationships can be exploited alongside genomic information to predict genetic traits with the aid of graph machine learning algorithms.
on Jun 19, 2020 in Genomics, Graphs, Machine Learning, Prediction
What is emotion AI and why should you care?
What is emotion AI, why is it relevant, and what do you need to know about it?
on Jun 19, 2020 in AI, Chatbot, Emotion, NLP, Sentiment Analysis
modelStudio and The Grammar of Interactive Explanatory Model Analysis
modelStudio is an R package that automates the exploration of ML models and allows for interactive examination. It works in a model agnostic fashion, therefore is compatible with most of the ML frameworks.
on Jun 19, 2020 in Analysis, Explainability, Interpretability, Machine Learning, R
6 Easy Steps to Implement a Computer Vision Application Using Tensorflow.js
In this article, we are going to see how we can implement computer vision applications using tensorflow.js models.
on Jun 18, 2020 in Computer Vision, Javascript, TensorFlow
The Most Important Fundamentals of PyTorch you Should Know
PyTorch is a constantly developing deep learning framework with many exciting additions and features. We review its basic elements and show an example of building a simple Deep Neural Network (DNN) step-by-step.
on Jun 18, 2020 in Deep Learning, Neural Networks, Python, PyTorch, Tensor
LightGBM: A Highly-Efficient Gradient Boosting Decision Tree
LightGBM is a histogram-based algorithm which places continuous values into discrete bins, which leads to faster training and more efficient memory usage. In this piece, we’ll explore LightGBM in depth.
on Jun 18, 2020 in Decision Trees, Gradient Boosting, Machine Learning, Python
Tom Fawcett, in memoriam
Foster Provost in memoriam for Tom Fawcett, killed on June 4th in a freak bicycle accident. Tom was a brilliant scholar, a selfless collaborator, a substantial contributor to Data Science for three decades, and a unique individual.
on Jun 17, 2020 in Foster Provost, History, Machine Learning, Tom Fawcett
Build Dog Breeds Classifier Step By Step with AWS Sagemaker
This post takes you through the basic steps for creating a cloud-based deep learning dog classifier, with everything accomplished from the AWS Management Console.
on Jun 17, 2020 in AWS, Dogs, Image Classification, Image Recognition, Sagemaker
A Classification Project in Machine Learning: a gentle step-by-step guide
Classification is a core technique in the fields of data science and machine learning that is used to predict the categories to which data should belong. Follow this learning guide that demonstrates how to consider multiple classification models to predict data scrapped from the web.
on Jun 17, 2020 in Beginners, Classification, Machine Learning
Crop Disease Detection Using Machine Learning and Computer Vision
Computer vision has tremendous promise for improving crop monitoring at scale. We present our learnings from building such models for detecting stem and wheat rust in crops.
on Jun 17, 2020 in Agriculture, Computer Vision, Deep Learning, fast.ai
Best Machine Learning Youtube Videos Under 10 Minutes
The Youtube videos on this list cover concepts such as what machine learning is, the basics of natural language processing, how computer vision works, and machine learning in video games.
on Jun 16, 2020 in Machine Learning, Video, Youtube
A Complete guide to Google Colab for Deep Learning
Google Colab is a widely popular cloud service for machine learning that features free access to GPU and TPU computing. Follow this detailed guide to help you get up and running fast to develop your next deep learning algorithms with Colab.
on Jun 16, 2020 in Deep Learning, GitHub, Google Colab, GPU, Jupyter
Simplified Mixed Feature Type Preprocessing in Scikit-Learn with Pipelines
There is a quick and easy way to perform preprocessing on mixed feature type data in Scikit-Learn, which can be integrated into your machine learning pipelines.
on Jun 16, 2020 in Data Preprocessing, Pipeline, Python, scikit-learn
Uber’s Ludwig is an Open Source Framework for Low-Code Machine Learning
The new framework allow developers with minimum experience to create and train machine learning models.
on Jun 15, 2020 in Low-Code, Machine Learning, No-Code, Open Source, Uber
Free Data Analytics Courses
Wherever your skills are at today, check out these top course recommendations for 2020 to help you master data analytics.
on Jun 15, 2020 in Courses, Data Analytics, Online Education
Understanding Machine Learning: The Free eBook
Time to get back to basics. This week we have a look at a book on foundational machine learning concepts, Understanding Machine Learning: From Theory to Algorithms.
on Jun 15, 2020 in Algorithms, Book, Free ebook, Machine Learning
Deploy a Machine Learning Pipeline to the Cloud Using a Docker Container
In this tutorial, we will use a previously-built machine learning pipeline and Flask app to demonstrate how to deploy a machine learning pipeline as a web app using the Microsoft Azure Web App Service.
on Jun 12, 2020 in Cloud, Docker, Machine Learning, Pipeline, PyCaret, Python
Five Cognitive Biases In Data Science (And how to avoid them)
Everyone is prey to cognitive biases that skew thinking, but data scientists must prevent them from spoiling their work. Learn more about five biases that can all too easily make your seemingly objective work become surprisingly subjective.
on Jun 12, 2020 in Advice, Bias, Cognitive Bias, Confirmation Bias, Data Science
Top 6 Reasons Data Scientists Should Know Java
There are many reasons why data scientists should learn Java. Read this overview of 6 specific reasons to help decide if Java might be right for your projects.
on Jun 12, 2020 in Data Science, Data Scientist, Java
Upgrading the Brand Mobile App with Machine Learning
The tech progress in mobile app development, as well as digital enhancements, have created new chances for brands to allure and retain customers. In bridging the individualization gap, Machine Learning comes to the rescue.
on Jun 11, 2020 in App, Machine Learning, Mobile
How to make AI/Machine Learning models resilient during COVID-19 crisis
COVID-19-driven concept shift has created concern over the usage of AI/ML to continue to drive business value following cases of inaccurate outputs and misleading results from a variety of fields. Data Science teams must invest effort in post-model tracking and management as well as deploy an agility in the AI/ML process to curb problems related to concept shift.
on Jun 11, 2020 in AI, Coronavirus, COVID-19, Machine Learning, Model Drift, Modeling
Math and Architectures of Deep Learning
This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 40% off Math and Architectures of Deep Learning with code nlkdarch40
on Jun 11, 2020 in Deep Learning, Manning, Mathematics
 Easy Speech-to-Text with Python
In this blog, I am demonstrating how to convert speech to text using Python. This can be done with the help of the “Speech Recognition” API and “PyAudio” library.
on Jun 10, 2020 in NLP, Python, Speech
Overview of data distributions
With so many types of data distributions to consider in data science, how do you choose the right one to model your data? This guide will overview the most important distributions you should be familiar with in your work.
on Jun 10, 2020 in Binomial, Distribution, Normal Distribution, Poisson Distribution, Probability, Statistics
Top May Stories: The Best NLP with Deep Learning Course is Free
Also: How to Think Like a Data Scientist; Python For Everybody: The Free eBook; Automated Machine Learning: The Free eBook.
on Jun 10, 2020 in Top stories
Count, the data notebook everyone can use
Dashboards have been the primary weapon of choice for distributing data over the last few decades, but they have brought with them a new set of problems. To increasingly democratise access to data we need to think again.
on Jun 9, 2020 in Dashboard, Data Science Platform, Jupyter
New Poll: What was the largest dataset you analyzed / data mined?
Take part in KDnuggets latest survey to have your voice heard, and let the community know what the largest dataset size you have worked with is.
on Jun 9, 2020 in Big Data, Datasets, Largest, Poll
GPT-3, a giant step for Deep Learning and NLP?
Recently, OpenAI announced a new successor to their language model, GPT-3, that is now the largest model trained so far with 175 billion parameters. Training a language model this large has its merits and limitations, so this article covers some of its most interesting and important aspects.
on Jun 9, 2020 in AI, Deep Learning, GPT-2, GPT-3, NLP, OpenAI
5 Essential Papers on Sentiment Analysis
To highlight some of the work being done in the field, here are five essential papers on sentiment analysis and sentiment classification.
on Jun 9, 2020 in NLP, Research, Sentiment Analysis, Text Classification
Natural Language Processing with Python: The Free eBook
This free eBook is an introduction to natural language processing, and to NLTK, one of the most prevalent Python NLP libraries.
on Jun 8, 2020 in Free ebook, NLP, NLTK, Python
Why Do AI Systems Need Human Intervention to Work Well?
All is not well with artificial intelligence-based systems during the coronavirus pandemic. No, the virus does not impact AI – however, it does impact humans, without whom AI and ML systems cannot function properly. Surprised?
on Jun 5, 2020 in AI, Coronavirus, Humans, Machine Learning, Watson
If you had to start statistics all over again, where would you start?
If you are just diving into learning statistics, then where do you begin? Find insight from those who have tread in these waters before, and see what they might have done differently along their personal journeys in statistics.
on Jun 5, 2020 in Advanced Statistics, Advice, Bayesian, Career Advice, Statistician, Statistics
Deep Learning for Detecting Pneumonia from X-ray Images
This article covers an end to end pipeline for pneumonia detection from X-ray images.
on Jun 5, 2020 in Deep Learning, Healthcare, Image Recognition, Python
Upcoming Webinars and Online Events in AI, Data Science, Machine Learning: June
Here are some interesting upcoming webinar, online events and virtual conferences in in AI, Data Science, and Machine Learning.
on Jun 4, 2020 in AI, Machine Learning, Meetings, Online Education, Virtual Event, Webinar
Machine Learning Experiment Tracking
Why is experiment tracking so important for doing real world machine learning?
on Jun 4, 2020 in Experimentation, Machine Learning, Python
5 Essential Papers on AI Training Data
Data pre-processing is not only the largest time sink for most Data Scientists, but it is also the most crucial aspect of the work. Learn more about training data and data processing tasks from 5 leading academic papers.
on Jun 4, 2020 in AI, Data Preparation, Data Preprocessing, Research, Training Data
Skills to Build for Data Engineering
This article jumps into the latest skill set observations in the Data Engineering Job Market which could definitely add a boost to your existing career or assist you in starting off your Data Engineering journey.
on Jun 4, 2020 in Career Advice, Data Engineering, Skills
Introduction to Convolutional Neural Networks
The article focuses on explaining key components in CNN and its implementation using Keras python library.
on Jun 3, 2020 in Convolutional Neural Networks, Keras, Neural Networks, Python
3 Key Data Science Questions to Ask Your Big Data
The process of understanding your data begins by asking 3 questions at the highest level, and then iteratively asking hundreds of cascading questions to get deeper insights.
on Jun 3, 2020 in Big Data, Business, Customer Analytics, Data Science, Metrics
From Languages to Information: Another Great NLP Course from Stanford
Check out another example of a Stanford NLP course and its freely available courseware.
on Jun 3, 2020 in Courses, NLP, Stanford
Four Ways to Apply NLP in Financial Services
Natural language processing (NLP) is increasingly used to review unstructured content or spot trends in markets. How is Refinitiv Labs applying NLP in financial services to meet challenges around investment decision-making and risk management?
on Jun 2, 2020 in Finance, NLP
Forecasting Stories 4: Time-series too, Causal too
This article is about the story of taking effective business decisions basis a combined model. Let us together study how these components work hand in hand.
on Jun 1, 2020 in Causality, Forecasting, Time Series
 Deep Learning for Coders with fastai and PyTorch: The Free eBook
If you are interested in a top-down, example-driven book on deep learning, check out the draft of the upcoming Deep Learning for Coders with fastai & PyTorch from fast.ai team.
on Jun 1, 2020 in Deep Learning, fast.ai, Free ebook, Jeremy Howard, PyTorch
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