TDAN
SEPTEMBER 3, 2019
As I write this, I can almost hear you wail “No, no, we don’t have too much metadata, we don’t have nearly enough! We have several projects in flight to expand our use of metadata.” Sorry, I’m going to have to disagree with you there. You are on a fool’s errand that will just provide […].
datapine
SEPTEMBER 4, 2019
The secret is out, and has been for a while: In order to remain competitive, businesses of all sizes, from startup to enterprise, need business intelligence (BI). Business intelligence has evolved into smart solutions that provide effective data management – from extracting, monitoring, analyzing, and deriving actionable insights needed to stay competitive on the market, to powerful visualizations created with a dashboard builder which enables business users to interact with data and drill into
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Andrew White
SEPTEMBER 4, 2019
For years theorists, economists, and even tech-evangelists, have all been arguing over the value of data. Notwithstanding the hype, even the Economist in 2017 suggested in a leader article that data was the new oil. Gartner has been writing about ‘data as an asset’ for years. We even ratified calculations to help determine and quantify the value of data assets.
Analytics Vidhya
SEPTEMBER 4, 2019
Overview What is p-value? Where is it used in data science? And how can we calculate it? We answer all these questions and more. The post Everything you Should Know about p-value from Scratch for Data Science appeared first on Analytics Vidhya.
Speaker: David Bard, Principal at VP Product Coaching
In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.
Corinium
SEPTEMBER 3, 2019
Mobile BI should extend your ability to discover, collaborate, and act on insights and create an inclusive and effective data culture. The best mobile apps have simple-to-use tools designed specifically with mobile in mind that mean you always know when, what and, importantly, why something changed in your data. Download your copy of 'Mobile-Focused BI: Using Automation to Cut Through the Clutter' to find out more on making analytic insights instantly actionable everywhere.
KDnuggets
SEPTEMBER 5, 2019
This blog summarizes the career advice/reading research papers lecture in the CS230 Deep learning course by Stanford University on YouTube, and includes advice from Andrew Ng on how to read research papers.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
SEPTEMBER 1, 2019
Overview Working on Data Science projects is a great way to stand out from the competition Check out these 7 data science projects on. The post Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills! appeared first on Analytics Vidhya.
Corinium
SEPTEMBER 4, 2019
Tell us about your experience in working with the data analytics community at TheMathCompany? Why do you like working in this space?
KDnuggets
SEPTEMBER 3, 2019
These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.
IBM Big Data Hub
SEPTEMBER 5, 2019
Among organizations investing in AI hardware, software or services, more will buy IBM and rely on Watson than any other vendor. This according to a new IDC report which names IBM as 2018’s market leader in AI. So just what sets apart IBM as leader of the AI provider pack?
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.
Analytics Vidhya
SEPTEMBER 2, 2019
Overview Learn how you can use computer vision and deep learning techniques to work with video data We will build our own video classification. The post Step-by-Step Deep Learning Tutorial to Build your own Video Classification Model appeared first on Analytics Vidhya.
Data Science 101
AUGUST 31, 2019
The competition site Kaggle has recently released some micro-courses aimed at helping people to quickly learn the skills of data science. It is called Kaggle Learn, Faster Data Science Education. It includes courses on: Python Deep Learning SQL and more. Check them out to quickly get up to speed. Happy Learning.
KDnuggets
SEPTEMBER 4, 2019
A recurring subject in NLP is to understand large corpus of texts through topics extraction. Whether you analyze users’ online reviews, products’ descriptions, or text entered in search bars, understanding key topics will always come in handy.
CIO Business Intelligence
SEPTEMBER 5, 2019
There is golden knowledge in the sea of data that businesses are swimming in. Being able to fish out the business intelligence you need — when you need it — is the key to steering your ship.
Speaker: Margaret-Ann Seger, Head of Product, Statsig
Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating
Analytics Vidhya
SEPTEMBER 3, 2019
Overview Learn the inner workings and math behind the HOG feature descriptor The HOG feature descriptor is used in computer vision popularly for object. The post Feature Engineering for Images: A Valuable Introduction to the HOG Feature Descriptor appeared first on Analytics Vidhya.
MLWhiz
SEPTEMBER 1, 2019
We as data scientists have gotten quite comfortable with Pandas or SQL or any other relational database. We are used to seeing our users in rows with their attributes as columns. But does the real world really behave like that? In a connected world, users cannot be considered as independent entities. They have got certain relationships between each other and we would sometimes like to include such relationships while building our machine learning models.
KDnuggets
SEPTEMBER 4, 2019
Recommender systems are an important class of machine learning algorithms that offer "relevant" suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches work along with implementations to follow from example code.
DataCamp
SEPTEMBER 3, 2019
Learn why Python is so important, and how it’s useful across industries and all fields of business analytics.
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Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.
IBM Big Data Hub
SEPTEMBER 6, 2019
The initial goal of sampling is to assess where the highest compliance risk areas are within your enterprise. Read blog to learn how IBM StoredIQ InstaScan accelerates this.
Smart Data Collective
SEPTEMBER 4, 2019
Maternal mortality rates in the United States jumped over 25% between 2000 and 2013. The CDC uses data to better understand why the United States has the highest maternal death rates in the developed world. Big data allows researchers to dig deeper into the issue to better understand what’s occurring that’s leading to increased deaths for mothers. Understaffed hospitals and medical errors are causing most of the deaths.
KDnuggets
SEPTEMBER 5, 2019
This is an interview between Rosaria Silipo and data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz, asking a few questions on the topic of automated machine learning from their point of view, and some interesting examples of its practical use.
Domino Data Lab
SEPTEMBER 3, 2019
This article covers how to perform hyperparameter optimization using a sequential model-based optimization (SMBO) technique implemented in the HyperOpt Python package. There is a complementary Domino project available. Introduction. Feature engineering and hyperparameter optimization are two important model building steps. Over the years, I have debated with many colleagues as to which step has more impact on the accuracy of a model.
Speaker: Jon Harmer, Product Manager for Google Cloud
Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.
Sisense
SEPTEMBER 5, 2019
Blog. For modern organizations, data is the ultimate building block. High profile companies are using data to build profitable new products, new lines of business, even entirely new industries. It’s the starting point and the finish line for every new business creation. In an age where every company is making moves to be more data-driven, those that figure out how to efficiently monetize their data insights will be the biggest winners.
BizAcuity
SEPTEMBER 5, 2019
Admit it or not, casinos are booming to become a much bigger playground for businesses. With most operating within a hotel-like framework, there are more ways to engage their customers than ever before. From an operational standpoint, this means that casino-owners need to deploy different systems in different places across the floor of the casino to ensure seamless functioning.
KDnuggets
SEPTEMBER 4, 2019
In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models.
IBM Big Data Hub
SEPTEMBER 5, 2019
What differentiates IBM Planning Analytics from other planning solutions? Quite a lot, actually. But today we’d like to focus on the practical, real-world benefits of just two key functions: data analysis and reporting.
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“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.
TDAN
SEPTEMBER 3, 2019
Are you worried about the security of your valuable data? Well, with the massive growth of business data in terms of complexity, volume and size, it is basic for worldwide associations to build up a strong data technique to address the main business needs. If you are working in an IT vertical then it is […].
BizAcuity
SEPTEMBER 5, 2019
Admit it or not, casinos are booming to become a much bigger playground for businesses. With most operating within a hotel-like framework, there are more ways to engage their customers than ever before. From an operational standpoint, this means that casino-owners need to deploy different systems in different places across the floor of the casino to ensure seamless functioning.
KDnuggets
SEPTEMBER 3, 2019
In this tutorial, you will learn how to run task scheduler to web scrape data from Lazada (eCommerce) website and dump it into SQLite RDBMS Database.
Smart Data Collective
SEPTEMBER 4, 2019
Big data is playing a big role in the commerce industry. Many experts believe it will be even more important in 2019. Big data is partially responsible for the 15% increase in ecommerce sales in 2018. Changing your data from one website or store to another is something that seems like a lot of work. However, if you pay attention to the data and other specifics when changing, you shouldn’t have any issues switching from one platform to another.
Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO
The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.
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