KDnuggets
NOVEMBER 28, 2019
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.
Data Science 101
DECEMBER 14, 2019
The fine folks at Microsoft have put together an excellent Single Page Cheatsheet for Azure Machine Learning Algorithms. It is very helpful for Azure, but it is also helpful for understanding when and why to use a particular algorithm. Microsoft’s Azure Machine Learning Algorithm Cheat Sheet. Start in the large blue box, “What do you want to do?
Hacker News
APRIL 14, 2019
Anyone who built software for a while knows that estimating how long something is going to take is hard. It’s hard to come up with an unbiased estimate of how long something will take, when fundamentally the work in itself is about solving something. One pet theory I’ve had for a really long time, is that some of this is really just a statistical artifact.
Analytics Vidhya
DECEMBER 15, 2019
Overview Neural fake news (fake news generated by AI) can be a huge issue for our society This article discusses different Natural Language Processing. The post An Exhaustive Guide to Detecting and Fighting Neural Fake News using NLP appeared first on Analytics Vidhya.
Speaker: Dr. Greg Loughnane and Chris Alexiuk
Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. They're often developing using prompting, Retrieval Augmented Generation (RAG), and fine-tuning (up to and including Reinforcement Learning with Human Feedback (RLHF)), typically in that order. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are le
Smart Data Collective
DECEMBER 2, 2019
Data science has shifted the existing ether bringing in new marvelous opportunities to many industries. In line with these immense possibilities, comes rapid changes and challenges. And in this case, the travel and tourism industry is no exception here. Travel industry may not be the first to inculcate emerging technology for its benefit, but it sure is benefiting from it now.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
DataRobot
MAY 15, 2019
Art is subjective and everyone has their own opinion about it. When I saw the expressionist painting Blue Poles , by Jackson Pollock, I was reminded of the famous quote by Rudyard Kipling, “It’s clever, but is it Art?” Pollock’s piece looks like paint messily spilled onto a drop sheet protecting the floor. The debate of what constitutes art has a long history that will probably never be settled, there is no definitive definition of art.
Dataconomy
NOVEMBER 24, 2019
An aspiration to create a data-driven future has resulted in massive data lakes, where even the most experienced data scientists can drown in. Today, it’s all about what you do with that data that determines your success. And IBM has the recipe for this. Read on. “Without data, you simply can’t. The post Here is how IBM’s Data Scientists look at Data-Driven Future appeared first on Dataconomy.
KDnuggets
DECEMBER 6, 2019
Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.
KDnuggets
DECEMBER 26, 2019
Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.
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Are you thinking of adding enhanced data matching and relationship detection to your product or service? Do you need to know more about what to look for when assessing your options? The Senzing Entity Resolution Buyer’s Guide gives you step-by-step details about everything you should consider when evaluating entity resolution technologies. You’ll learn about use cases, technology and deployment options, top ten evaluation criteria and more.
KDnuggets
DECEMBER 3, 2019
What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.
KDnuggets
NOVEMBER 28, 2019
This article will walk through an extractive text summarization process, using a simple word frequency approach, implemented in Python.
KDnuggets
DECEMBER 31, 2019
With so many buzzwords surrounding AI and machine learning, understanding which can bring business value and which are best left in the lab to mature is difficult. While machine learning offers significant power in driving digital transformations, a business must start with the right questions and leave the math to the development teams.
KDnuggets
DECEMBER 19, 2019
The third part in a series on leveraging techniques to take a look inside the black box of AI, this guide considers methods that try to explain each prediction instead of establishing a global explanation.
KDnuggets
DECEMBER 18, 2019
Ready to try to get hired as a data scientist for the first time? Avoiding these common mistakes won’t guarantee an offer, but not avoiding them is a sure fire way for your application to be tossed into the trash bin.
KDnuggets
DECEMBER 4, 2019
What is Explainability in AI and how can we leverage different techniques to open the black box of AI and peek inside? This practical guide offers a review and critique of the various techniques of interpretability.
KDnuggets
NOVEMBER 27, 2019
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.
KDnuggets
DECEMBER 5, 2019
Increase your confidence to perform data cleaning with a broader perspective of what datasets typically look like, and follow this toolbox of code snipets to make your data cleaning process faster and more efficient.
KDnuggets
NOVEMBER 5, 2019
Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work.
KDnuggets
OCTOBER 7, 2019
Are you looking to learn natural language processing? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to learning NLP and its varied topics.
KDnuggets
SEPTEMBER 17, 2019
We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.
KDnuggets
AUGUST 23, 2019
Entirely implemented with NumPy, this extensive tutorial provides a detailed review of neural networks followed by guided code for creating one from scratch with computational graphs.
KDnuggets
AUGUST 16, 2019
As a data scientist, you are in high demand. So, how can you increase your marketability even more? Check out these current trends in skills most desired by employers in 2019.
KDnuggets
AUGUST 8, 2019
Graph Machine Learning uses the network structure of the underlying data to improve predictive outcomes. Learn how to use this modern machine learning method to solve challenges with connected data.
KDnuggets
OCTOBER 22, 2019
For full-stack data science mastery, you must understand data management along with all the bells and whistles of machine learning. This high-level overview is a road map for the history and current state of the expansive options for data storage and infrastructure solutions.
KDnuggets
DECEMBER 12, 2019
Python's plotting libraries such as matplotlib and seaborn does allow the user to create elegant graphics as well, but lack of a standardized syntax for implementing the grammar of graphics compared to the simple, readable and layering approach of ggplot2 in R makes it more difficult to implement in Python.
KDnuggets
AUGUST 29, 2019
The sample data used for training has to be as close a representation of the real scenario as possible. There are many factors that can bias a sample from the beginning and those reasons differ from each domain (i.e. business, security, medical, education etc.).
KDnuggets
NOVEMBER 12, 2019
While Pandas is the library for data processing in Python, it isn't really built for speed. Learn more about the new library, Modin, developed to distribute Pandas' computation to speedup your data prep.
KDnuggets
SEPTEMBER 9, 2019
This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.
KDnuggets
SEPTEMBER 23, 2019
Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.
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