Analytics Vidhya
MAY 12, 2019
Introduction Data scientists spend close to 70% (if not more) of their time cleaning, massaging and preparing data. That’s no secret – multiple surveys. The post A Beginner’s Guide to Tidyverse – The Most Powerful Collection of R Packages for Data Science appeared first on Analytics Vidhya.
Dataconomy
MAY 23, 2019
AI is a tricky subject to wrap your head around, that is why we talked to experts of IBM. We were enlightened by Romeo Kienzler, head of IoT at IBM and frequent speaker at Data Natives. Next, Matthias Biniok, lead Watson Architect DACH at IBM, who designed CIMON, the smiling. The post Why we need to open up AI black boxes right now appeared first on Dataconomy.
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Data Science 101
MAY 20, 2019
I took and passed the exam during the beta period. These are my memories of the topics on the exam. You can get this information as the Microsoft Azure Data Scientist Checklist. General Overview. Below is the basic structure of the DP-100: Designing and Implementing a Data Science Solution on Azure. Passing the exam will qualify you for the Azure Data Scientist Associate certification.
Smart Data Collective
MAY 20, 2019
We’re well past the point of realization that big data and advanced analytics solutions are valuable — just about everyone knows this by now. In fact, there’s no escaping the increasing reliance on such technologies. Big data alone has become a modern staple of nearly every industry from retail to manufacturing, and for good reason. IDC predicts that if our digital universe or total data content were represented by tablets, then by 2020 they would stretch all the way to the moon over six times.
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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?
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.
Eugene Yan
MAY 10, 2019
OMSCS CS7646 (Machine Learning for Trading) - Don't sell your house to trade algorithmically.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Dataconomy
MAY 23, 2019
Design thinking continues to be all the rage amongst organizations of all kinds – from academia to startups, to agencies and consultancies, or large enterprises. The concept is popular today not because it’s new per se, but its approach to problem-solving fits well with the digital transformation that companies are. The post Three Critical Aspects of Design Thinking for Big Data Solutions appeared first on Dataconomy.
Data Science 101
MAY 31, 2019
Avrim Blum, John Hopcroft, and Ravindran Kannan wrote the book, Foundations of Data Science (PDF download). It is free and available for download. It can be useful for academic work or in business. It covers topics such as: Machine Learning Massive Data Clustering and many more. See the video for more.
Smart Data Collective
MAY 2, 2019
Large companies around the world are investing in big data. Big data has been especially important for optimizing their marketing campaigns. However, a number of small businesses are getting in on the action too. Local marketing agencies have discovered that SEO is more dependent on big data than ever. They are developing more data driven solutions to offer better search marketing strategies.
DataRobot
MAY 2, 2019
So, you have successfully trained a machine learning model after choosing the best algorithm and high-quality training data. Time to celebrate, right? Not quite!
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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.
DataRobot Blog
MAY 7, 2019
by Jen Underwood. Artificial intelligence (AI) and machine learning can deliver unprecedented value to the business. Unfortunately, fantastic findings often get lost in translation. From expressing metrics in unfamiliar terminology to presenting odd. Read More.
Analytics Vidhya
MAY 2, 2019
Introduction What is one of the most important and core concepts of statistics that enables us to do predictive modeling, and yet it often. The post Statistics 101: Introduction to the Central Limit Theorem (with implementation in R) appeared first on Analytics Vidhya.
Dataconomy
MAY 29, 2019
Chatbots help customers to resolve their issues at a blazing speed but the one of the main questions is whether the business should opt for a rule-based bot or an AI- based bot. Chatbots are not new in the technological arena. They are a lot smarter now than their predecessors. The post Rule-Based Bots or AI Bots? Which One Do You Prefer? appeared first on Dataconomy.
Data Science 101
MAY 6, 2019
Sponsored Post by T.J. DeGroat of Springboard. At Springboard , we recently sat down with Michael Beaumier, a data scientist at Google, to discuss his transition into the field, what the interview process is like, the future of data wrangling, and the advice he has for aspiring data professionals. The full video Q&A is below, but here are some of the highlights.
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.
Smart Data Collective
MAY 29, 2019
Big data is completely transforming the way we live and the way companies conduct business. Pretty much every industry you can think of uses some form of big data technology to help optimize their business. In this article, we reveal five industries which have been reshaped by big data technology. 1. Retail. IBM wrote an excellent report about the use of big data in the retail sector.
DataRobot
MAY 7, 2019
As more and more companies rely on AI , people are questioning whether or not AI can be trusted. Business reputations are damaged when inscrutable black box AI systems make mistakes or make biased decisions. To avoid these issues, organizations are seeking out ways to apply best practices of AI governance to ensure that AIs are following business rules and making sensible and trustworthy decisions.
Victor Zhou
MAY 29, 2019
In this post, we’re going to do a deep-dive on something most introductions to Convolutional Neural Networks (CNNs) lack: how to train a CNN , including deriving gradients, implementing backprop from scratch (using only numpy ), and ultimately building a full training pipeline! This post assumes a basic knowledge of CNNs. My introduction to CNNs (Part 1 of this series) covers everything you need to know, so I’d highly recommend reading that first.
Analytics Vidhya
MAY 7, 2019
Introduction I love descriptive statistics. Visualizing data and analyzing trends is one of the most exciting aspects of any data science project. But what. The post Extracting and Analyzing 1000 Basketball Games using Pandas and Chartify 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
MAY 29, 2019
Was this a transition year for data protection? How much were the fines collected in the first year of GDPR? What regulations have been enforced so far? Here is all you want to know about GDPR, after a year of its implementation. The European Commission started in January 2012. The post One year of GDPR: What has changed or what hasn’t? appeared first on Dataconomy.
Data Science 101
MAY 23, 2019
Here is the latest data science news for May 2019. From Data Science 101. REAL TALK WITH A DATA SCIENTIST: THE FUTURE OF DATA WRANGLING WHAT IS ON THE MICROSOFT DATA SCIENCE CERTIFICATION EXAM? General Data Science. Microsoft Build 2019 – This is a huge conference hosted by Microsoft for the developer community. Many of the presentation are available to watch online.
Smart Data Collective
MAY 8, 2019
If you’re a marketer or business owner in today’s competitive marketplace, you’ve probably tried just about everything you can think of to maximize your success. You’ve dabbled in digital marketing, visited trade shows, paid for print advertising, and incentivized customer testimonials. It’s probably resulted in lots of stress, sleepless nights, and CBD oil drops to give you the energy and focus to keep going.
DataRobot
MAY 3, 2019
Retail is one of the many industries that is embracing AI and seeing exponential results. “.AI in retail is expected to witness a growth in spending of over 200% between 2019 and 2023. The projections reveal that it will be $12 billion in spending by 2023.” ( MartechSeries ) Retailers around the world are leveraging AI throughout their entire organizations to improve demand forecasting, customer experience, and targeted campaigns.
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.
Victor Zhou
MAY 24, 2019
I had the privilege of joining Adam Stacoviak and Jerod Santo on an episode of The Changelog recently to discuss the explosion of the.io game genre, as well as my experiences building and selling.io games like generals.io and geoarena.online (no longer online). Check it out: The Changelog 347: Creating and selling multiplayer online games – Listen on Changelog.com If you want to learn more about building.io games, I’ve written guides on this topic: How to Build a Multiplayer (.io) Web Game, Part
Analytics Vidhya
MAY 5, 2019
Introduction “How did your neural network produce this result?” This question has sent many data scientists into a tizzy. It’s easy to explain how. The post A Guide to Understanding Convolutional Neural Networks (CNNs) using Visualization appeared first on Analytics Vidhya.
Dataconomy
MAY 10, 2019
Breaking down the workforce options for AI developers to structure raw data for machine learning. Here is a look. While it may seem like artificial intelligence (AI) has hit the big time, a lot of work needs to be done before its potential really come to life. In our modern. The post The Right Workforce Turns Data into Rocket Fuel for AI Projects appeared first on Dataconomy.
Data Science 101
MAY 3, 2019
Occasionally a product in Microsoft Azure will go down. Luckily, Azure has a status page to tell you which servers and services are down. Here is a quick video to help you find that status page.
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.
Smart Data Collective
MAY 6, 2019
Self-driving cars and trucks once seemed like a staple of science fiction which could never morph into a reality here in the real world. Nevertheless, the past few years have given rise to a number of impressive innovations in the field of autonomous vehicles that have turned self-driving cars from a funny idea into a marketing gimmick and finally into a full-fledged reality of the modern roadway.
DataRobot
MAY 27, 2019
This blog is meant to be a fun and unique take on predicting which team will win the Stanley Cup 2019.
Victor Zhou
MAY 3, 2019
This is Part 2 of my “How to Build a Multiplayer (.io) Web Game” series - make sure you read Part 1 first. In this post, we’ll take a look at the Node.js backend powering our example.io game : On mobile, it works best fullscreen at [link] As a reminder, here’s what we went over in Part 1 of the series: Project Overview / Structure : A high level view of the project.
Analytics Vidhya
MAY 28, 2019
Introduction I love reading and decoding machine learning research papers. There is so much incredible information to parse through – a goldmine for us. The post Decoding the Best Papers from ICLR 2019 – Neural Networks are Here to Rule 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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