Jan
2020 Feb
All (80) | Events (7) | News, Education (4) | Opinions (17) | Top Stories, Tweets (9) | Tutorials, Overviews (43)
- Can Edge Analytics Become a Game Changer?
- Feb 28, 2020.
Edge analytics is considered to be the future of sensor handling, and this article discusses its benefits and architecture of modern edge devices, gateways, and sensors. Deep Learning for edge analytics is also considered along with a review of experiments in human and chess figure detection using edge devices.
-
The Big Bad NLP Database: Access Nearly 300 Datasets
- Feb 28, 2020.
Check out this database of nearly 300 freely-accessible NLP datasets, curated from around the internet. - Hands on Hyperparameter Tuning with Keras Tuner
- Feb 28, 2020.
Or how hyperparameter tuning with Keras Tuner can boost your object classification network's accuracy by 10%.
- Decision Tree Intuition: From Concept to Application
- Feb 27, 2020.
While the use of Decision Trees in machine learning has been around for awhile, the technique remains powerful and popular. This guide first provides an introductory understanding of the method and then shows you how to construct a decision tree, calculate important analysis parameters, and plot the resulting tree.
- New Poll: When Will AutoML Replace Data Scientists (if ever)?
- Feb 27, 2020.
Take part in the latest KDnuggets poll by weighing in on when you think AutoML and Automated Data Science will replace humans — if ever.
- Introducing fastpages: An easy to use blogging platform with extra features for Jupyter Notebooks
- Feb 27, 2020.
This article introduces the easy to use blogging platform fastpages. fastpages relies on Github pages for hosting, and Github Actions to automate the creation of your blog, and contains extra features for Jupyter Notebooks.
- Top KDnuggets tweets, Feb 19-25: 9 lessons learned during my first year as a #DataScientist
- Feb 26, 2020.
Also The Next Decade in #AI: Four Steps Towards Robust #ArtificialIntelligence; Perl, yes, but will R be dead by 2030? #rstats Programming Languages You Won’t Use by 2030; Will AutoML eliminated Data Scientists? Let's do some tests to find out...Leaders, Changes, and Trends in Gartner 2020 #MagicQuadrant for #DataScience
- Data Science Curriculum for self-study
- Feb 26, 2020.
Are you asking the question, "how do I become a Data Scientist?" This list recommends the best essential topics to gain an introductory understanding for getting started in the field. After learning these basics, keep in mind that doing real data science projects through internships or competitions is crucial to acquiring the core skills necessary for the job.
- Image Recognition and Object Detection in Retail
- Feb 26, 2020.
“According to Gartner, by 2020, 85% of customer interactions in the retail industry will be managed by AI.”
- Python and R Courses for Data Science
- Feb 26, 2020.
Since Python and R are a must for today's data scientists, continuous learning is paramount. Online courses are arguably the best and most flexible way to upskill throughout ones career.
- Probability Distributions in Data Science
- Feb 26, 2020.
Some machine learning models are designed to work best under some distribution assumptions. Therefore, knowing with which distributions we are working with can help us to identify which models are best to use.
-
Learning from 3 big Data Science career mistakes
- Feb 25, 2020.
Thinking of data science as merely a technical profession, like programming, may take you away from your goals. We explain big mistakes to avoid, including not understanding the 2 cultures of statistics, and not understanding the shift to industrial focus. - Francois Chollet on the Future of Keras and Reinforce Conference
- Feb 25, 2020.
Ahead of Reinforce Conference in Budapest, we asked Francois Chollet, the creator of Keras, about Keras future, proposed developments, PyTorch, energy efficiency, and more. Listen to him in person in Budapest, April 6-7, and use code KDNuggets to save 15% on conference tickets.
-
Free Mathematics Courses for Data Science & Machine Learning
- Feb 25, 2020.
It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond. - Audio Data Analysis Using Deep Learning with Python (Part 2)
- Feb 25, 2020.
This is a followup to the first article in this series. Once you are comfortable with the concepts explained in that article, you can come back and continue with this.
- Not-to-Miss at PAW Industry 4.0: GE, Shell, Nanotronics
- Feb 24, 2020.
Data scientists, industrial planners, and other machine learning experts will meet in Las Vegas on May 31 - Jun 4. Don’t miss this once-a-year opportunity to hear from leading thinkers and practitioners at Predictive Analytics World for Industry 4.0. Use the code KDNUGGETS for a 15% discount.
- Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms
- Feb 24, 2020.
The Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms has the largest number of leaders ever. We examine the leaders and changes and trends vs previous years.
- Top Stories, Feb 17-23: The Death of Data Scientists will AutoML replace them?
- Feb 24, 2020.
Also: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1); Audio Data Analysis Using Deep Learning with Python (Part 1); Hand labeling is the past. The future is #NoLabel AI; Googles Data Science Interview Brain Teasers
- 7 Data Trends for 2020 (and one non-trend)
- Feb 24, 2020.
This article discusses trends that will (and won't) take shape in 2020.
- Microsoft Open Sources ZeRO and DeepSpeed: The Technologies Behind the Biggest Language Model in History
- Feb 24, 2020.
The two efforts enable the training of deep learning models at massive scale.
- Prepare for a Long Battle against Deepfakes
- Feb 21, 2020.
While deepfakes threaten to destroy our perception of reality, the tech giants are throwing down the gauntlet and working to enhance the state of the art in combating doctored videos and images.
- Passive Data Collection and Actionable Results: What to Know
- Feb 21, 2020.
There are plenty of ways to get actionable results by using passive data. However, such an outcome will not happen without careful forethought. Data analysts must consider several crucial specifics, including what questions they want and expect the information to answer, and how they'll apply the findings to aid the business.
- How Kubeflow Can Add AI to Your Kubernetes Deployments
- Feb 21, 2020.
As Kubernetes is capable of working with other solutions, it is possible to integrate it with a collection of tools that can almost fully automate your development pipeline. Some of those third-party tools even allow you to integrate AI into Kubernetes. One such tool you can integrate with Kubernetes is Kubeflow. Read more about it here.
-
The Death of Data Scientists – will AutoML replace them?
- Feb 20, 2020.
Soon after tech giants Google and Microsoft introduced their AutoML services to the world, the popularity and interest in these services skyrocketed. We first review AutoML, compare the platforms available, and then test them out against real data scientists to answer the question: will AutoML replace us? - The Forgotten Algorithm
- Feb 20, 2020.
This article explores Monte Carlo Simulation with Streamlit.
- Data Science Influencers and Keynotes Coming to ODSC East 2020
- Feb 20, 2020.
ODSC is proud to announce its keynote speakers for ODSC East 2020, Apr 13-17 in Boston — ten preeminent researchers and visionaries who will kick off the already expert lineup set to speak at the community-based event for data science practitioners and AI engineers.
- In Loving Memory of Strictly-Typed Schemas
- Feb 20, 2020.
This article addresses one very peculiar manifestation of marketing propaganda in the big data industry that has crippled data engineers across the board — a resolute and methodical undermining of the sanctity of strictly-typed schemas.
- Top KDnuggets tweets, Feb 12-18: What Does it Mean to Deploy a #MachineLearning Model?
- Feb 19, 2020.
Also: A minimalist drawing that represents closeness over time. Captures the span of life with bittersweet accuracy; How much is a Data Scientist's salary in 2020?; Great set of #NLP Interview Questions #DeepLearning; 12-Hour Machine Learning Challenge: Build & deploy an app with Streamlit and DevOps tools
- 2020 INFORMS Business Analytics Conference: Where the Wild West meets the future of analytics innovation
- Feb 19, 2020.
From April 26-28, more than 1,000 leading analytics professionals and industry experts will gather in Denver to explore the newest mathematical solutions to some of industry’s largest challenges.
- Hand labeling is the past. The future is #NoLabel AI
- Feb 19, 2020.
Data labeling is so hot right now… but could this rapidly emerging market face disruption from a small team at Stanford and the Snorkel open source project, which enables highly efficient programmatic labeling that is 10 to 1,000x as efficient as hand labeling?
- Getting Started with R Programming
- Feb 19, 2020.
An end to end Data Analysis using R, the second most requested programming language in Data Science.
-
Audio Data Analysis Using Deep Learning with Python (Part 1)
- Feb 19, 2020.
A brief introduction to audio data processing and genre classification using Neural Networks and python. - Hot topics at PAW Healthcare: Predicting Ebola Outbreaks, Improving Hospital Patient Flow & more
- Feb 18, 2020.
Predictive Analytics World for Healthcare, May 31-Jun 4 in Las Vegas, is packed with sessions across Healthcare Business Operations and Clinical applications. Witness how data science and machine learning are employed at leading enterprises, resulting in improved outcomes, lower costs, and higher patient satisfaction. Use the code KDNUGGETS for a 15% discount on your Deep Learning World ticket.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)
- Feb 18, 2020.
2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.
- Using the Fitbit Web API with Python
- Feb 18, 2020.
Fitbit provides a Web API for accessing data from Fitbit activity trackers. Check out this updated tutorial to accessing this Fitbit data using the API with Python.
- Seize Your New Career in Data Science
- Feb 17, 2020.
Springboard’s mission has always been to enable everyone to attain their full potential by preparing students for the ever-changing world around them You can start working towards your dream data science career and land a new role by the end of summer.
- Scaling the Wall Between Data Scientist and Data Engineer
- Feb 17, 2020.
The educational and research focuses of machine learning tends to highlight the model building, training, testing, and optimization aspects of the data science process. To bring these models into use requires a suite of engineering feats and organization, a standard for which does not yet exist. Learn more about a framework for operating a collaborative data science and engineering team to deploy machine learning models to end-users.
- Using AI to Identify Wildlife in Camera Trap Images from the Serengeti
- Feb 17, 2020.
With recent developments in machine learning and computer vision, we acquired the tools to provide the biodiversity community with an ability to tap the potential of the knowledge generated automatically with systems triggered by a combination of heat and motion.
- Top Stories, Feb 10-16: Why Did I Reject a Data Scientist Job?; Fourier Transformation for a Data Scientist
- Feb 17, 2020.
Also: Math for Programmers – your guide for solving math problems in code; What Does it Mean to Deploy a Machine Learning Model?; Deep Neural Networks; Easy Image Dataset Augmentation with TensorFlow; Intent Recognition with BERT using Keras and TensorFlow 2
- Inside The Machine Learning that Google Used to Build Meena: A Chatbot that Can Chat About Anything
- Feb 17, 2020.
Meena is one of the major milestones in the history of NLU. How did Google build it?
- Deep Neural Networks
- Feb 14, 2020.
We examine the features and applications of a deep neural network.
- What Does it Mean to Deploy a Machine Learning Model?
- Feb 14, 2020.
You are a Data Scientist who knows how to develop machine learning models. You might also be a Data Scientist who is too afraid to ask how to deploy your machine learning models. The answer isn't entirely straightforward, and so is a major pain point of the community. This article will help you take a step in the right direction for production deployments that are automated, reproducible, and auditable.
- Fourier Transformation for a Data Scientist
- Feb 14, 2020.
The article contains a brief intro into Fourier transformation mathematically and its applications in AI.
- Introduction to Geographical Time Series Prediction with Crime Data in R, SQL, and Tableau
- Feb 14, 2020.
When reviewing geographical data, it can be difficult to prepare the data for an analysis. This article helps by covering importing data into a SQL Server database; cleansing and grouping data into a map grid; adding time data points to the set of grid data and filling in the gaps where no crimes occurred; importing the data into R; running XGBoost model to determine where crimes will occur on a specific day
- Analytics Summit 2020: Real World Applications of Business Analytics, April 6-8, Cincinnati
- Feb 13, 2020.
The 8th annual Analytics Summit 2020, sponsored by the University of Cincinnati’s Center for Business Analytics, will be held on Apr 6-8, including two analytics training days and a Conference featuring speakers presenting real world applications of data science and business analytics.
- Adversarial Validation Overview
- Feb 13, 2020.
Learn how to implement adversarial validation that builds a classifier to determine if your data is from the training or testing sets. If you can do this, then your data has issues, and your adversarial validation model can help you diagnose the problem.
- Practical Hyperparameter Optimization
- Feb 13, 2020.
An introduction on how to fine-tune Machine and Deep Learning models using techniques such as: Random Search, Automated Hyperparameter Tuning and Artificial Neural Networks Tuning.
- Easy Image Dataset Augmentation with TensorFlow
- Feb 13, 2020.
What can we do when we don't have a substantial amount of varied training data? This is a quick intro to using data augmentation in TensorFlow to perform in-memory image transformations during model training to help overcome this data impediment.
- Top KDnuggets tweets, Feb 05-11: #SciPy 1.0: fundamental algorithms for scientific computing in #Python; Why is Data Science so popular?
- Feb 12, 2020.
Why is Data Science so Popular?; Visual Paper Summary: ALBERT (A Lite BERT); Uber Has Assembled One of the Most Impressive Open Source DL Stacks; Top #AI Influencers To Follow in 2020
- Math for Programmers – your guide for solving math problems in code
- Feb 12, 2020.
Math for Programmers teaches you the math you need to know for a career in programming, concentrating on what you need to know as a developer.
- Why Did I Reject a Data Scientist Job?
- Feb 12, 2020.
Snagging that job as a Data Scientist might not be exactly what you were expecting. Consider this advice on carefully considering job titles with what the position might really be like day-to-day.
- Sharing your machine learning models through a common API
- Feb 12, 2020.
DEEPaaS API is a software component developed to expose machine learning models through a REST API. In this article we describe how to do it.
- Illustrating the Reformer
- Feb 12, 2020.
In this post, we will try to dive into the Reformer model and try to understand it with some visual guides.
- Top January Stories: How to land a Data Scientist job at your dream company; I wanna be a data scientist, but … how?
- Feb 11, 2020.
Also: The Book to Start You on Machine Learning; Top 5 must-have Data Science skills for 2020.
- Fidelity on How to Find a Tailor-Fit Unicorn Data Scientist
- Feb 11, 2020.
Predictive Analytics World for Financial Services in Las Vegas, May 31-Jun 4 is honored to host an exceptional keynote by Fidelity Investments’ AI and Data Science Center of Excellence Leader, Victor Lo: "How to Find a Tailor-Fit 'Unicorn' Data Scientist for Financial Services". Use the code KDNUGGETS for a 15% discount on your Predictive Analytics World ticket.
- How to learn data science on your own: a practical guide
- Feb 11, 2020.
While much focus today is on the rise in working from home and the challenges experienced, not as much is said about learning from home. For those lone wolfs studying Data Science in a self-directed way, a range of issues can get in the way of your goal. Learn about these common problems to prepare to focus yourself all the way to your educational goals.
- Basics of Audio File Processing in R
- Feb 11, 2020.
This post provides basic information on audio processing using R as the programming language. It also walks through and understands some basics of sound and digital audio.
- Recommender System Metrics: Comparing Apples, Oranges and Bananas
- Feb 11, 2020.
This article will discuss a sometimes-overlooked aspect of what distinguishes recommender systems from other machine learning tasks: added uncertainties of measuring them.
- Observability for Data Engineering
- Feb 10, 2020.
Going beyond traditional monitoring techniques and goals, understanding if a system is working as intended requires a new concept in DevOps, called Observability. Learn more about this essential approach to bring more context to your system metrics.
- Intent Recognition with BERT using Keras and TensorFlow 2
- Feb 10, 2020.
TL;DR Learn how to fine-tune the BERT model for text classification. Train and evaluate it on a small dataset for detecting seven intents. The results might surprise you!
- Top Stories, Feb 3-9: 12-Hour Machine Learning Challenge: Build & deploy an app with Streamlit and DevOps tools; The Future of Machine Learning Will Include a Lot Less Engineering
- Feb 10, 2020.
Also: The Data Science Puzzle — 2020 Edition; Top 5 Data Science Trends for 2020; How to land a Data Scientist job at your dream company; Audio File Processing: ECG Audio Using Python
- Amazon Uses Self-Learning to Teach Alexa to Correct its Own Mistakes
- Feb 10, 2020.
The digital assistant incorporates a reformulation engine that can learn to correct responses in real time based on customer interactions.
- AI and Machine Learning In Our Every Day Life
- Feb 7, 2020.
The curiosity and buzz around the most talked-about technology -- Artificial Intelligence -- have experts and technophiles busy decoding its exciting future applications. Of course, the use of AI and machine learning is already pervasive in our daily lives, as we review many of these popular features in this article.
- Large Scale Adversarial Representation Learning
- Feb 7, 2020.
GANs can be used for unsupervised learning where a generator maps latent samples to generate data, but this framework does not include an inverse mapping from data to latent representation. BiGAN adds an encoder E to the standard generator-discriminator GAN architecture — the encoder takes input data x and outputs a latent representation z of the input.
- The Data Science Puzzle — 2020 Edition
- Feb 7, 2020.
The data science puzzle is once again re-examined through the relationship between several key concepts of the landscape, incorporating updates and observations since last time. Check out the results here.
- Understanding Density-based Clustering
- Feb 6, 2020.
HDBSCAN is a robust clustering algorithm that is very useful for data exploration, and this comprehensive introduction provides an overview of its fundamental ideas from a high-level view above the trees to down in the weeds.
- The Future of Machine Learning Will Include a Lot Less Engineering
- Feb 6, 2020.
Despite getting less attention, the systems-level design and engineering challenges in ML are still very important — creating something useful requires more than building good models, it requires building good systems.
- Getting up and Running with Python: Installing Anaconda on Windows
- Feb 6, 2020.
This tutorial covers how to download and install Anaconda on Windows; how to test your installation; how to fix common installation issues; and what to do after installing Anaconda.
- Top KDnuggets tweets, Jan 29 – Feb 04: 30 Python Best Practices, Tips, And Tricks; 7 Books to Grasp Math of Data Science and ML
- Feb 5, 2020.
The cost of obtaining a MSc in #DataScience in Europe; 30 Python Best Practices, Tips, And Tricks; OpenAI is Adopting PyTorch; I wanna be a data scientist, but... how?
- Intro to Machine Learning and AI based on high school knowledge
- Feb 5, 2020.
Machine learning information is becoming pervasive in the media as well as a core skill in new, important job sectors. Getting started in the field can require learning complex concepts, and this article outlines an approach on how to begin learning about these exciting topics based on high school knowledge.
- Create Your Own Computer Vision Sandbox
- Feb 5, 2020.
This post covers a wide array of computer vision tasks, from automated data collection to CNN model building.
- Optimal Estimation Algorithms: Kalman and Particle Filters
- Feb 5, 2020.
An introduction to the Kalman and Particle Filters and their applications in fields such as Robotics and Reinforcement Learning.
- Do You Trust and Understand Your Predictive Models?
- Feb 4, 2020.
To help practitioners make the most of recent and disruptive breakthroughs in debugging, explainability, fairness, and interpretability techniques for machine learning read “An Introduction to Machine Learning Intrepretability Second Edition”. Download this report now.
- Top 5 Data Science Trends for 2020
- Feb 4, 2020.
As Data Science continues to expand into the next decade, this article features five important trends in the field that are expected in 2020. Leverage these trends to help improve your business processes for maximizing growth.
- Audio File Processing: ECG Audio Using Python
- Feb 4, 2020.
In this post, we will look into an application of audio file processing, for a good cause — Analysis of ECG Heart beat and write code in python.
- Serverless Machine Learning with R on Cloud Run
- Feb 4, 2020.
Expedite the deployment of your machine models using serverless cloud infrastructure. In this tutorial, we explore creating and deploying a model which scraps real time Twitter data and returns interactive visualization using R.
- Why are Machine Learning Projects so Hard to Manage?
- Feb 3, 2020.
What makes deploying a machine learning project so difficult? Is it the expectations? The people? The tech? There are common threads to these challenges, and best practices exist to deal with them.
- Top Stories, Jan 27 – Feb 2: How to land a Data Scientist job at your dream company; How to Optimize Your Jupyter Notebook
- Feb 3, 2020.
Also: Data Validation for Machine Learning; OpenAI is Adopting PyTorch… They Aren’t Alone; I wanna be a data scientist, but how?; Top 10 AI, Machine Learning Research Articles to know; Google Dataset Search Provides Access to 25 Million Datasets
- Microsoft Open Sources Jericho to Train Reinforcement Learning Using Linguistic Games
- Feb 3, 2020.
The new framework provides an OpenAI-like environment for language-based games.
- 12-Hour Machine Learning Challenge: Build & deploy an app with Streamlit and DevOps tools
- Feb 3, 2020.
This article will present the knowledge, process, tools, and frameworks required for completing a 12-hour ML challenge. I hope you can find it useful for your personal or professional projects.
