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.
Analytics Vidhya
AUGUST 6, 2019
Overview Real-time object detection is taking the computer vision industry by storm Here’s a step-by-step introduction to SlimYOLOv3, the latest real-time object detection framework. The post A Friendly Introduction to Real-Time Object Detection using the Powerful SlimYOLOv3 Framework appeared first on Analytics Vidhya.
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Dataconomy
AUGUST 9, 2019
When considering the growth and productivity of organizations in different fields, it doesn’t take too much time to see a pattern on how maintenance strategies are common throughout all consistently thriving operations. Predictive maintenance is amongst the most impactful of strategy plans because it centers itself on forecasting issues before. The post Which Industries Reap The Biggest Benefits From Predictive Maintenance And Why appeared first on Dataconomy.
Hacker News
AUGUST 7, 2019
Incessantly annoying and fraudulent robocalls. Corrupt wireless company employees taking hundreds of thousands of dollars in bribes to unlock and hijack mobile phone service. Wireless providers selling real-time customer location data, despite repeated promises to the contrary. A noticeable uptick in SIM-swapping attacks that lead to multi-million dollar cyberheists.
Speaker: Tamara Fingerlin, Developer Advocate
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
KDnuggets
AUGUST 7, 2019
Learn about Artificial Neural Networks, Deep Learning, Recurrent Neural Networks and LSTMs like never before and use NLP to build a Chatbot!
Analytics Vidhya
AUGUST 5, 2019
Overview Evaluating a model is a core part of building an effective machine learning model There are several evaluation metrics, like confusion matrix, cross-validation, The post 11 Important Model Evaluation Metrics for Machine Learning Everyone should know appeared first on Analytics Vidhya.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Eugene Yan
AUGUST 3, 2019
OMSCS CS6440 (Intro to Health Informatics) - A primer on key tech and standards in healthtech.
KDnuggets
AUGUST 7, 2019
Benford’s law is a little-known gem for data analytics. Learn about how this can be used for anomaly or fraud detection in scientific or technical publications.
Analytics Vidhya
AUGUST 7, 2019
Overview Language models are a crucial component in the Natural Language Processing (NLP) journey These language models power all the popular NLP applications we. The post A Comprehensive Guide to Build your own Language Model in Python! appeared first on Analytics Vidhya.
Smart Data Collective
AUGUST 8, 2019
Big data is the lynchpin of new advances in cybersecurity. Unfortunately, predictive analytics and machine learning technology is a double-edged sword for cybersecurity. Hackers are also exploiting this technology, which means that there is a virtual arms race between cybersecurity companies and black hat cybercriminals. Datanami has talked about the ways that hackers use big data to coordinate attacks.
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
DataRobot
AUGUST 5, 2019
Comcast’s third annual PHLAI Conference - taking place on August 15th at the Comcast Technology Center in Philadelphia - will be focused around using artificial intelligence and machine learning to improve the customer experience. As the industry leader in machine learning, with hundreds of use cases focusing on improving the customer experience across all industries, DataRobot was invited to present at the conference, with a session led by Gourab De, DataRobot’s VP of Data Science.
KDnuggets
AUGUST 6, 2019
In this story, we’re going to take an aerial tour of optimization with Lagrange multipliers. When do we need them? Whenever we have an optimization problem with constraints.
Analytics Vidhya
AUGUST 4, 2019
Overview Singular Value Decomposition (SVD) is a common dimensionality reduction technique in data science We will discuss 5 must-know applications of SVD here and. The post Master Dimensionality Reduction with these 5 Must-Know Applications of Singular Value Decomposition (SVD) in Data Science appeared first on Analytics Vidhya.
Smart Data Collective
AUGUST 9, 2019
It’s no secret that everything businesses need to grow and accomplish their vision is theirs for the taking. But like anything that yields powerful results, the process doesn’t come easy. This describes the dilemma many organizations are facing when it comes to getting insights out of data. But before enterprises can shore up their analytics processes, they need to understand what’s holding them back.
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
Victor Zhou
AUGUST 8, 2019
Keras is a simple-to-use but powerful deep learning library for Python. In this post, we’ll build a simple Convolutional Neural Network (CNN) and train it to solve a real problem with Keras. This post is intended for complete beginners to Keras but does assume a basic background knowledge of CNNs. My introduction to Convolutional Neural Networks covers everything you need to know (and more) for this post - read that first if necessary.
KDnuggets
AUGUST 6, 2019
Feature selection is one of the most important tasks in machine learning. Learn how to use a simple random search in Python to get good results in less time.
Depends on the Definition
AUGUST 4, 2019
Deep learning models have shown amazing performance in a lot of fields such as autonomous driving, manufacturing, and medicine, to name a few. However, these are fields in which representing model uncertainty is of crucial importance.
Smart Data Collective
AUGUST 9, 2019
Big data in the gaming industry has played a phenomenal role in the field. We have previously talked about the benefits of using big data by gaming providers that offer cash games, such as slots. However, more mainstream games use big data as well. Fortnite is one of the games that uses big data to offer great service to its customers. Even Forbes Tech Council has written about the benefits of data lakes in Fortnite.
Speaker: Frank Taliano
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
Victor Zhou
AUGUST 4, 2019
Today is my 6 month anniversary of starting this blog! ? In my First 50 Days of Blogging post, I outlined some (rather ambitious) goals for my first year of blogging (Year One): Publish 50 blog posts. Get a million pageviews. Grow my newsletter to 10,000 subscribers. Here’s where I’m at as of today: Published 24 blog posts. Gotten 314k pageviews. Grown my newsletter to 2,000 subscribers.
KDnuggets
AUGUST 7, 2019
There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics; however, many algorithms sprout from the most established algorithms, e.g. ordinary least squares, gradient boosting, support vector machines, tree-based algorithms and neural networks.
DataRobot
AUGUST 8, 2019
You can’t appreciate the good without first going through the difficult.
Smart Data Collective
AUGUST 7, 2019
We have talked extensively about the fields that rely most heavily on big data. The insurance industry is one of the companies investing the most in big data technology. Exactly one year ago today, SNS Telecom & IT published a report highlighting the demand for big data in the insurance industry. The report showed that insurers spent $2.4 billion on big data in 2018 alone.
Speaker: Chris Townsend, VP of Product Marketing, Wellspring
Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?
Explosion
AUGUST 6, 2019
:black_circle: A spaCy pipeline and model for NLP on unstructured legal text. - GitHub - ICLRandD/Blackstone: :black_circle: A spaCy pipeline and model for NLP on unstructured legal text.
KDnuggets
AUGUST 8, 2019
Simply put, data science is an attempt to understand given data using the scientific method. That's why data science is a scientific discipline. You are free (and encouraged!) to apply data science to business use cases, just as you are encouraged to apply it to many other domains.
KDnuggets
AUGUST 9, 2019
Image segmentation is the classification of an image into different groups. Many kinds of research have been done in the area of image segmentation using clustering. In this article, we will explore using the K-Means clustering algorithm to read an image and cluster different regions of the image.
KDnuggets
AUGUST 5, 2019
This is an excerpt from a survey which sought to evaluate the relevance of machine learning in operations today, assess the current state of machine learning adoption and to identify tools used for machine learning. A link to the full report is inside.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
KDnuggets
AUGUST 5, 2019
Over the past many months, I’ve received hundreds of messages from people asking me how they could get started with Data Science. Therefore, I thought it would be useful to write down a framework for those wanting to get started with Data Science.
KDnuggets
AUGUST 7, 2019
In this tutorial, you’ll use Python and Pandas to explore a dataset and create visual distributions, identify and eliminate outliers, and uncover correlations between two datasets.
KDnuggets
AUGUST 6, 2019
Check out this video (and Jupyter notebook) which outlines a number of Pandas tricks for working with and manipulating data, covering topics such as string manipulations, splitting and filtering DataFrames, combining and aggregating data, and more.
KDnuggets
AUGUST 7, 2019
Also: Ten more random useful things in R you may not know about; 5 Probability Distributions Every Data Scientist Should Know; Machine Learning is Happening Now: A Survey of Organizational Adoption, Implementation, and Investment; Programmers rejoice! Deep TabNine offer code autocompletion with #deeplearning.
Speaker: Tamara Fingerlin, Developer Advocate
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
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