Analytics Vidhya
APRIL 22, 2020
Overview Python is a superb language for data science but not everyone is a Python expert Here, we present 7 Python hacks that’ll help. The post 7 Python Hacks, Tips and Tricks for Data Science Projects appeared first on Analytics Vidhya.
Dataconomy
APRIL 1, 2020
The promise of artificial intelligence (AI) is finally being realized across a wide variety of industries. AI is now viewed as a crucial technology to adopt for enterprises to thrive in today’s business environment. Healthcare, in particular, has been one of the industries that AI advocates expect to be revolutionized. The post Key Challenges That Healthcare AI Needs to Overcome in 2020 appeared first on Dataconomy.
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Smart Data Collective
APRIL 10, 2020
Artificial Intelligence (AI) is changing the way that eCommerce companies do business. AI is being implemented in systems across the eCommerce sector. From generating leads to gathering information, AI has improved multiple facets of the industry. Algorithmic bots have revolutionized customer facing services. Automated systems are the driving force behind improvements in back-end eCommerce software. eCommerce AI is a data-driven trend that allows companies to manage and analyze consumer informat
DataRobot
APRIL 10, 2020
The world is going through extremely turbulent times. With the ongoing disruption of our lives, communities, and businesses from the COVID-19 pandemic, predictions from existing machine learning models trained prior to the pandemic become less reliable. There is plenty of historical data, but historical examples from before the pandemic may not provide the relevant examples needed to train a model that is useful today.
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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?
Eugene Yan
APRIL 25, 2020
What I learned about measuring diversity, novelty, surprise, and serendipity from 10+ papers.
Data Science 101
APRIL 6, 2020
Brandon Rohrer is an expert in neural networks and deep learning. Plus, he makes really excellent videos about the topic. His entire YouTube Channel is worth viewing. How Deep Neural Networks Work by Brandon Rohrer. The post Brandon Rohrer – How Deep Neural Networks Work appeared first on Data Science 101.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Dataconomy
APRIL 16, 2020
Editor’s Note: The article was originally published by Wendell Santos, the editor at ProgrammableWeb.com. Check back there as the article will continue to be updated as new APIs related to COVID-19 are made available. Over the past two months, as COVID-19 has proliferated, ProgrammableWeb has been tracking APIs that provide access to data related.
Smart Data Collective
APRIL 13, 2020
Big data is crucial for any organization that wants to attract and retain customers. A study by McKinsey Global Institute found that data-driven companies are 400% more likely to retain customers and 2,200% more likely to acquire new ones. Back in 2011, my colleagues and I first started discussing the evolving standards of customer service in business.
Hacker News
APRIL 26, 2020
In the fall of 1999 I got the biggest productivity boost of my entire career as a software developer. In the October issue of IEEE Computer magazine, there was an article by Kent Beck called “Embracing change with extreme programming” In it, he outlined Extreme Programming (XP), which includes much of what we now refer to as agile development.
DataRobot
APRIL 1, 2020
Our objective is to predict the severity of a COVID-19 patient at time of hospital admission , to provide a second opinion to the triaging officer, so that more resources can be accurately allocated to a serious case [1]. We define a serious case as a patient having at least 11 days of hospitalisation which is equal to or more than the average stay of a serious COVID-19 case [2], or died in hospital.
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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
Eugene Yan
APRIL 11, 2020
Should I join a start-up? Which offer should I accept? A simple metaphor to guide your decisions.
Analytics Vidhya
APRIL 19, 2020
Overview Looking to crack your next deep learning interview? You’ve come to the right place! We have put together a list of popular deep. The post A Comprehensive Guide to 21 Popular Deep Learning Interview Questions and Answers appeared first on Analytics Vidhya.
Dataconomy
APRIL 17, 2020
Hacking Health Berlin, Charité University Hospital Berlin, the Berlin Institute of Health, Data Natives and Vision Health Pioneers brought together 164 participants, and 20 hacking teams that produced 14 community-sourced tech solutions to meet the COVID-19-related needs of Germany’s leading clinicians and researchers. Let’s take a look at the results.
Smart Data Collective
APRIL 10, 2020
Machine learning is leading to numerous changes in the energy industry. The Department of Energy recently announced that it is taking steps to accelerate the integration of machine learning technology in energy research and development. The head of the Department of Energy announced that they will be investing $30 million in artificial intelligence and machine learning algorithms.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
Kaggle
APRIL 20, 2020
I participated in the R package recommendation engine competition on Kaggle for two reasons. First, I use R a lot. I cannot learn statistics without R. This competition is my chance to give back to the community a R package recommendation engine. Second, during my day job as an engineer behind a machine learning service in the cloud, product recommendation is one of the most popular applications our early adopters want to use the web service for.
DataRobot
APRIL 2, 2020
Visual AI is New in DataRobot 6.0. In Release 6.0 of DataRobot , we are thrilled to announce a ground-breaking new capability in our Automated Machine Learning product. DataRobot Visual AI gives you the ability to easily incorporate image data into your machine learning models alongside tabular and text-based data types. This enables your organization to get value from computer vision, right away – all with the same DataRobot usability, workflow, visuals, and other UI features you know and love.
Eugene Yan
APRIL 4, 2020
Using a Zettelkasten helps you make connections between notes, improving learning and memory.
Analytics Vidhya
APRIL 29, 2020
Overview Deploying your machine learning model is a key aspect of every ML project Learn how to use Flask to deploy a machine learning. The post How to Deploy Machine Learning Models using Flask (with Code!) appeared first on Analytics Vidhya.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Dataconomy
APRIL 2, 2020
Five experts went live with educational sessions at our community site DN Club and told us about technology in times of coronavirus. Where are we heading in the crisis and how can the tech community contribute to finding solutions? Even though we are moving towards difficult times, there might be. The post How Coronavirus can make open-source movements flourish and fix our healthcare systems appeared first on Dataconomy.
Smart Data Collective
APRIL 10, 2020
90% of all data in the world has been generated in the last two years. With that in mind, it’s not surprising that a lot of companies are struggling with structuring and making sense of the data that they have, which causes various organizational issues, as well as limits the potential growth. That’s why big data companies that can help use that data are in such high demand.
Alation
APRIL 23, 2020
The post Supporting Remote Workers with a Data Catalog in the WFH Era appeared first on Alation.
DataRobot
APRIL 6, 2020
If you’re a regular reader of the DataRobot blog, you likely fall into one of two categories. Perhaps you’re a data scientist who’s looking for ideas about how to get started with advanced time series forecasting , information about our expanded support for deep learning , or maybe just some ideas on how you can automate some of the data science tasks you dread.
Speaker: Kevin Kai Wong, President of Emergent Energy Solutions
In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.
Eugene Yan
APRIL 17, 2020
Why you should give a talk and some tips from five years of speaking and hosting meet-ups.
Analytics Vidhya
APRIL 8, 2020
Introduction Google Colab is an amazing gift to the data science community from the fine folks at Google. Colab gives us the ability to. The post 5 Amazing Google Colab Hacks You Should Try Today! appeared first on Analytics Vidhya.
Dataconomy
APRIL 9, 2020
The global COVID-19 pandemic has generated a wide variety of responses from citizens, governments, charities, organizations, and the startup community worldwide. At the time of writing, the number of confirmed cases has now exceeded 1,000,000, affecting 204 countries and territories. From mandated lockdowns to applauding health workers from balconies, a.
Smart Data Collective
APRIL 8, 2020
sThe recent years have seen a tremendous surge in data generation levels , characterized by the dramatic digital transformation occurring in myriad enterprises across the industrial landscape. The amount of data being generated globally is increasing at rapid rates. In fact, studies by the Gigabit Magazine depict that the amount of data generated in 2020 will be over 25 times greater than it was 10 years ago.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.
Kaggle
APRIL 20, 2020
I graduated on Warsaw University of Technology with master thesis about text mining topic (intelligent web crawling methods). I work for Polish IT consulting company (Sollers Consulting), where I develop and design various insurance industry related stuff, (one of them is insurance fraud detection platform). From time to time I try to compete in data mining contests (Netflix, competitions on Kaggle and tunedit.org) — from my perspective it is a very good way to get real data mining experience.
DataRobot
APRIL 8, 2020
Deploying models into production remains a critical challenge for organizations adopting AI. For many custom-built models, deployment requires extensive data science knowledge and coding expertise to promote those models from development to production. With varied languages and frameworks across AI teams and projects, deployment becomes even more challenging and specialized, depleting critical resources from data science and IT teams alike.
DeepMind
APRIL 5, 2020
Under a microscope, a pane of window glass doesn’t look like a collection of orderly molecules, as a crystal would, but rather a jumble with no discernable structure. Glass is made by starting with a glowing mixture of high-temperature melted sand and minerals. Once cooled, its viscosity (a measure of the friction in the fluid) increases a trillion-fold, and it becomes a solid, resisting tension from stretching or pulling.
Analytics Vidhya
APRIL 2, 2020
Introduction to Feature Scaling I was recently working with a dataset that had multiple features spanning varying degrees of magnitude, range, and units. This. The post Feature Scaling for Machine Learning: Understanding the Difference Between Normalization vs. Standardization appeared first on Analytics Vidhya.
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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.
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