KDnuggets
JANUARY 16, 2020
With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond.
Analytics Vidhya
JANUARY 28, 2020
Overview Understand the structure of a Machine Learning Pipeline Build an end-to-end ML pipeline on a real-world data Train a Random Forest Regressor for. The post Build your first Machine Learning pipeline using scikit-learn! appeared first on Analytics Vidhya.
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Dataconomy
JANUARY 30, 2020
Patient privacy and safety have always been cornerstones of the U.S. healthcare system. But in today’s digital era, there are apps tracking the most sensitive information such as the female menstrual cycle and fertility window. The collection of this data might be valuable for the future of healthcare – the. The post Can Femtech deliver radically personalized care to women?
DataRobot
JANUARY 27, 2020
In Super Bowl LIV this Sunday, the Kansas City Chiefs will face the San Francisco 49ers in Miami, Florida. This will be the first Super Bowl appearance for the Chiefs in 50 years. After a loss in 2013, the 49ers are looking to secure their sixth Super Bowl ring, which would tie them with the New England Patriots and Pittsburgh Steelers for the league record.
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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?
Data Science 101
JANUARY 24, 2020
It was an exciting cloud data science week. Lots of interesting stuff to cover, so let’s get started. News. Microsoft DP-100 Certification Updated – The Microsoft Data Scientist certification exam has been updated to cover the latest Azure Machine Learning tools. Google Dataset Search goes GA – search and discover millions of datasets Google Cloud GPU Price Cut – Google reduces the prices of NVIDIA T4 GPUs which should save some money for people doing AI PyTorch 1.4 Relea
Eugene Yan
JANUARY 12, 2020
Beating the baseline using Graph & NLP techniques on PyTorch, AUC improvement of ~21% (Part 2 of 2).
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Analytics Vidhya
JANUARY 26, 2020
Overview Regular Expressions or Regex is a versatile tool that every Data Scientist should know about Regex can automate various mundane data processing tasks. The post 4 Applications of Regular Expressions that every Data Scientist should know (with Python code)! appeared first on Analytics Vidhya.
Dataconomy
JANUARY 14, 2020
Organizations implementing AI have increased by 270 per cent over the last four years, according to a recent survey by Gartner. Even though the implementation of AI is a growing trend, 63 per cent of organizations haven’t deployed this technology. What is holding them back: cost, talent shortage? For many. The post How can you be AI ready? appeared first on Dataconomy.
DataRobot
JANUARY 10, 2020
Does your organization apply appropriate human resources governance when hiring staff? Large enterprises tend to follow the same basic processes for hiring human staff. First, hiring managers write a job description, including the tasks the position requires and the skills and attributes of a suitable candidate. Job vacancies are posted, sometimes recruiters are also used, and people submit their resumes for consideration.
Data Science 101
JANUARY 29, 2020
Previously, we looked at some Challenges of Data Science Projects. They can be difficult, and they do not alway succeed. Below are 3 techniques to help your next project become a data science success. 1. Start with a Plan. If you don’t know where you are going, you might end up someplace else. Yogi Berra. This quote by Yogi is humorous, but it is true.
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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.
Machine Learning (Theory)
JANUARY 4, 2020
This blog has been quiet for the last year. I have quite a bit to write about but found myself often out of time between work at Microsoft, ICML duties, and family life. Nevertheless, I expect to get back to more substantive discussions as I adjust to the new load. In the meantime, I’ve updated the site in various ways: SSL now works, and mail for people registering new accounts should work again.
KDnuggets
JANUARY 7, 2020
Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.
Analytics Vidhya
JANUARY 14, 2020
Overview Looking to transition into data science? Here are 5 paths for a non-data science person to land a role in this space The. The post 5 Thoughts on How to Transition into Data Science from Different Backgrounds appeared first on Analytics Vidhya.
Dataconomy
JANUARY 23, 2020
How are various organizations handling the accelerating transition of data to the cloud? What are the obstacles in data cleaning for analytics and the time constraints companies face when preparing data for analytics, AI and Machine Learning (ML) initiatives? Here is a look at some insights from a recent report. The post Why over one-third of AI and Analytics Projects in the Cloud fail?
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.
DataRobot
JANUARY 22, 2020
As always too common, retail is often written about as an industry that is in decline and needs triple bypass heart surgery to bring it back to the good old days where stores were packed with excited customers ready to spend their hard-earned cash. It is hard to argue that retail is not in a tough period when so many retailers continue to close unprofitable stores and we see some legendary brands going out of business altogether.
Data Science 101
JANUARY 17, 2020
Some news this week out of Microsoft and Amazon. News. Azure is now ISO/IEC 27701 Certified Azure becomes the first public cloud to receive this certification for Privacy and Information Management Python in Visual Studio Code Visual Studio Code now allows a user to select which version of python should be used for the Jupyter Notebook AWS Quick Start now deploys Matillion ETL for Amazon Redshift Title says it all, but if you use Matillion and Redshift, this is a big win for you.
Smart Data Collective
JANUARY 17, 2020
Big Data has a lot of great uses in the work of consumer marketing. Experts recognize that its benefits go well beyond the needs of individual consumers. In fact, Big Data has many uses in helping patient lives in the world of healthcare. The market for big data in healthcare is growing 22% a year. From predicting risk factors to helping cure disease, Big Data in healthcare is multi-faceted.
KDnuggets
JANUARY 9, 2020
This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.
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.
Analytics Vidhya
JANUARY 19, 2020
Overview Singleton scalar for missing values Dedicated datatype for strings Improved output formats and data summaries Introduction There are only a handful of. The post Pandas Version 1.0 is Out! Top 4 Features Every Data Scientist Should Know appeared first on Analytics Vidhya.
Dataconomy
JANUARY 6, 2020
Which are the industries that are likely to be impacted the most by alternative web data this year ? Here is a look. For the past few years, financial institutions, such as hedge fund managers, have been on the forefront of harnessing the power of alternative data solutions to help. The post Here are the Sweet Spots for Alternative Web Data in 2020 appeared first on Dataconomy.
DataRobot
JANUARY 31, 2020
Climate change and catastrophic weather phenomena dominated much of the global headlines in 2019, with devastating reports of earthquakes, hurricanes, and other powerful forces of nature destroying homes and lives. Some of the starkest images were those of raging wildfires that wiped out not only homes but also huge swathes of natural land, from Australia to California and dozens of other countries in between.
Data Science 101
JANUARY 22, 2020
DP 100 Updated! Microsoft has updated the Data Science Certification exam. I took the exam about a year ago and it was a bit out of date back then. It should now match the current focus and tools on Azure. I have covered my experience and what topics are on the exam. Those blog posts were for the old exam which focused on the legacy Azure Machine Learning Studio interface and general data science knowledge.
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.
Smart Data Collective
JANUARY 24, 2020
Have you ever heard of the most effective DevOps e.g. Development Operations practices? If you haven’t, then you should start to care about implementing DevOps infrastructure into your business as it helps to deliver applications or any software faster and effectively while spending fewer team efforts. Furthermore, thanks to such benefits this field of development is growing very fastly and it’s critically important to optimize your product delivery and maintenance that can be done through imple
KDnuggets
JANUARY 7, 2020
An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.
Analytics Vidhya
JANUARY 27, 2020
Overview Learn how to perform text classification using PyTorch Understand the key points involved while solving text classification Learn to use Pack Padding feature. The post Build Your First Text Classification model using PyTorch appeared first on Analytics Vidhya.
Dataconomy
JANUARY 29, 2020
What does the cloud industry has to offer for the year 2020? What are the trends we will see in cloud adoption and cloud-to-cloud migration? How will 5G impact cloud adoption? Read on. The global economic outlook has been lukewarm heading into 2020, yet there is much reason for confidence. The post Thriving SaaS Growth and Containerization Use Will Drive Cloud Market in 2020 appeared first on Dataconomy.
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.
Eugene Yan
JANUARY 5, 2020
Building a baseline recsys based on data scraped off Amazon. Warning - Lots of charts! (Part 1 of 2).
Data Science 101
JANUARY 31, 2020
Welcome to Cloud Data Science 5. There were not as many announcements as last week in Cloud Data Science 4 , but quantity is not what is important. The first announcement is big! Let’s get started. News. The Pandas library goes 1.0 Yes, it had not been at version 1.0 yet. Version 1.0 does not bring any major architectural changes. It marks a commintment by the community and development team.
Smart Data Collective
JANUARY 20, 2020
It goes without saying that blogging has slowly and steadily evolved into an indispensable marketing tool. While marketers have been continually using the best possible strategies to improve the existing global blogging landscape, the inclusion of artificial intelligence has taken the ballgame to a whole different level. Moreover, blogging is one marketing activity that needs to be initiated flawlessly for massive returns and any deviation from the perfect path can readily diminish the gains and
KDnuggets
JANUARY 20, 2020
It’s easy to say "I wanna be a data scientist," but. where do you start? How much time is needed to be desired by companies? Do you need a Master’s degree? Do you need to know every mathematical concept ever derived? The journey might be long, but follow this plan to help you keep moving forward toward your career goal.
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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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