Smart Data Collective

OCTOBER 11, 2023

We mentioned that Python is one of the best programming languages for data science and AI applications. It offers a wealth of tools and features that empower developers to craft responsive, interactive, and visually stunning user interfaces. Angular’s architecture enables efficient rendering and data binding.

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CIO Business Intelligence

NOVEMBER 20, 2023

Take AVA, the AI-infused customer support bot that AirAsia introduced in 2019. While it may currently be too risky to let a generative AI bot directly interact with customers without a human in the loop, their synthetic language capabilities can be used to glow up existing customer service bots. Think of it as “My Fair Chatbot.”

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Interactive Risk ROI Testing 117

Business Over Broadway

DECEMBER 20, 2018

The importance of data science and machine learning continues to grow in business and beyond. I did my part this year to spread interest in data science to more people. Below are my top 10 blog posts of 2018: Favorite Data Science Blogs, Podcasts and Newsletters. Click image to enlarge.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

Data Science 101

DECEMBER 12, 2019

It is Computer Science Education Week and in 2019 Machine Learning and Artificial Intelligence are two of the most popular and influential topics in technology. Training Data Bias Prediction Machine Learning AI. Here is the first video, but most of the training is very interactive and fun.

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Smart Data Collective

SEPTEMBER 30, 2019

Machine learning and other big data technology has rendered password security a greater concern. Password Security in the Age of Big Data. Alexander Polyakov of Towards Data Science discussed some of the ways that they are using machine learning to exploit their victims. Hackers are becoming more tech-savvy than ever.

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Machine Learning Big Data Risk Interactive 71

O'Reilly on Data

MAY 21, 2019

As the number of data scientists and machine learning engineers grow within an organization, tools have to be standardized, models and features need to be shared, and automation starts getting introduced. 58% of survey respondents indicated they are building or evaluating data science platforms. Data results from a Twitter poll.

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datapine

DECEMBER 4, 2019

These systems can already speak, write, read and learn; hence, this is one of the big data buzzwords that will continue to disrupt industries in 2020 as well. As we mentioned in our business intelligence buzzwords article for 2019 , mobile usage is becoming an increasing factor in BI. Mobile Analytics.

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CIO Business Intelligence

OCTOBER 4, 2023

The fourth is called the merchant, consumer, and developer experience layer, which includes the web interface, mobile applications, and APIs that allow customers to use PayPal’s service interactively and programmatically. This is considered the heart, the closest thing to customers.

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Digital Transformation Deep Learning Data Lake Risk 122

Rocket-Powered Data Science

MARCH 10, 2020

In 2019, I was asked to write the Foreword for the book “ Graph Algorithms: Practical Examples in Apache Spark and Neo4j “ , by Mark Needham and Amy E. I wrote an extensive piece on the power of graph databases, linked data, graph algorithms, and various significant graph analytics applications.

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Metadata Machine Learning ROI Prescriptive Analytics 250

O'Reilly on Data

JANUARY 25, 2021

The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. We’ve explored usage across all publishing partners and learning modes, from live training courses and online events to interactive functionality provided by Katacoda and Jupyter notebooks. What about data science?

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Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. The approach they’ve used applies to other popular data science APIs such as NumPy , Tensorflow , and so on.

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Metadata Machine Learning Data Science Data-driven 105

Smarten

AUGUST 23, 2022

How many donuts were sold in Scottsdale, Arizona during Thanksgiving 2019 and 2018? c) that Az means Arizona and that d) last year was 2019. It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP by offering tools that users will want to leverage and interacting with users in a way that is meaningful to them.

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Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. back to the structure of the dataset. Let’s look through some antidotes. Ergo, less interpretable.

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Machine Learning Data Science Modeling Visualization 105

Insight

AUGUST 17, 2020

The Remote Experience While this was the first session for Insight in which all Fellows participated remotely, we’ve been offering a remote data science program since 2015. Kim Vo (Coaching & Development Lead, Interview Strategy Team) and Emily Kearney (Program Director, Data Science) during the fall session, September 2019.

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Data Science Data Processing Cost-Benefit Strategy 63

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

TF Lattice offers semantic regularizers that can be applied to models of varying complexity, from simple Generalized Additive Models, to flexible fully interacting models called lattices, to deep models that mix in arbitrary TF and Keras layers. The drawback of GAMs is that they do not allow feature interactions.

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Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Sci Foo 2019.

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datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2019 was a particularly major year for the business intelligence industry. We all gained access to the cloud.

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Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science.

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Domino Data Lab

SEPTEMBER 9, 2019

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. That’s excellent for supporting really interesting workflow integrations in data science work. Usually it’s human-generated text, but not always. get_data(). ?corpus

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Deep Learning Machine Learning Data Science Visualization 110

AWS Big Data

JUNE 14, 2023

The AWS Professional Services (ProServe) Insights team builds global operational data products that serve over 8,000 users within Amazon. Our team was formed in 2019 as an informal group of four analysts who supported ad hoc analysis for a division of ProServe consultants. Outside of work, Ameya is a professional pilot.

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The Unofficial Google Data Science Blog

APRIL 23, 2024

However, if we experiment with both parameters at the same time we will learn something about interactions between these system parameters. Interactions between parameters in different YouTube recommendation subsystems definitely exist, but important interactions and quadratic effects seem relatively rare.

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bridgei2i

NOVEMBER 20, 2020

That brings us to the end of this wonderful interaction. Do subscribe to our channel as we continue to bring to you the latest in all things AI, through interactions with experts and thought leaders in our upcoming episodes till then goodbye, stay home and stay safe. So, I would say yes, very relevant in current times. Monica: Okay.

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Risk Management Risk Management Metrics 92

FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. It is a database query language for accessing data and querying, updating, and managing relational database systems.

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Smarten

JUNE 15, 2022

The reason they can do this is simple: the tools provided for this purpose are designed for human interaction. Ask a question that reveals ‘most’ or ‘least’, ‘high’ or ‘low’: What was the highest temperature in Arizona in 2019 and when did it happen? They know how to search for something on Google and get the results they need.

Analytics 52

Analytics ROI Data-driven Sales 52

Jen Stirrup

APRIL 2, 2019

Research evidence has shown that consumers interact with advertising in complex ways, especially since we have such short attention spans (Weilbacher, 2003). For example, over at Data Relish, we mix mature Business Intelligence technologies with new and upcoming technology, Artificial Intelligence is enjoying rapid growth (Xiong, 2019).

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Marketing Advertising Data-driven Strategy 60

Business Over Broadway

MAY 22, 2019

Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration. How employees can drive transformation and emerging technology adoption: Both are data-heavy endeavors; We know that statistics/math knowledge is related to data science project success.

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Smart Data Collective

JULY 24, 2019

Rostering software is available to operations of all varieties, and should be on top of every manager’s wishlist in 2019. If you aren’t sold on the solution yet, then here is why rostering software is a valuable asset in 2019. The post Data Science Offers Fascinating New Scheduling Solutions appeared first on SmartData Collective.

Data Science 76

Data Science Big Data Software Data-driven 76

Insight

NOVEMBER 14, 2019

Snapshot of interactive visualization of the topics identified by Guided LDA and the keywords in each topic (pyLDAvis) Originally posted on A nalytics Vidhya. The prevalent use of online platforms for interaction and the large size of the text data from users’ input makes digesting data increasingly more time-consuming.

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Testing Modeling Strategy Interactive 54

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

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Data Governance Machine Learning Metadata Big Data 84

Insight

NOVEMBER 16, 2018

We are now designing and refining the tools that will allow all 7 billion people on earth to interact and transact without borders. This will be a free, full-time, 7 week fellowship based in San Francisco, starting March 2019.

Internet of Things 75

Internet of Things Cost-Benefit Technology Testing 75

datapine

OCTOBER 21, 2020

Summing up the product of all this work, the data science team developed a web-based user interface that forecasts patient loads and helps in planning resource allocation by utilizing online data visualization that reaches the goal of improving the overall patients’ care. 2) Electronic Health Records (EHRs).

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Andrew White

JANUARY 11, 2021

As such a head of analytics, BI and data science may emerge. Are you anticipating continued separation of “BI/Analytics” teams from “Data Science” teams or are those roles merging in the years ahead? Many data science labs are set up as shared services. That’s the idea.

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Data Analytics Analytics Data-driven Finance 52

CIO Business Intelligence

APRIL 15, 2022

But according to the UK’s Turing Institute, a national center for data science and AI, the predictive tools made little to no difference. In March 2016, Microsoft learned that using Twitter interactions as training data for machine learning algorithms can have dismaying results.

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Smart Data Collective

OCTOBER 14, 2019

Regardless of if you’re a data science professional or an IT department who wants to help your company have more successful data science projects, it’s essential to have some data science tools under your belt to avail of when needed. Here are some open-source options to consider.

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Data Science Machine Learning Big Data Interactive 67

CIO Business Intelligence

JULY 24, 2023

For example, Subway IT has helped drive digital sales up 500% from 2019 to 2023, thanks to its work on Subway’s own digital channels as well as with third-party food delivery services, Herlihy says. Those are activities where the IT team can really prove their value, because they can only be done with the right technologies in place.

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IT Sales Business Objectives Marketing 86

Depict Data Studio

SEPTEMBER 17, 2019

Chris Lysy is a professional data designer and illustrator constantly exploring the overlap between contemporary design practice, digital communications, and data science. David focuses especially on helping researchers embrace the power of the internet to communicate with online, interactive reporting. Chris Lysy.

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