WEBINAR: Augmented Analytics for Today’s Business User - 7 May 2020

Data Science Central Webinar Series Event

Augmented Analytics for Today’s Business User Join us for the latest DSC Webinar on May 7th, 2020 Augmented Analytics is no longer the future – it's now. The next generation of BI and analytics is here, and it relies heavily on AI. But with all the hype, there’s confusion about how to move forward. All too often, companies choose one-size-fits-all approaches or rely too heavily on closed, “black-box” algorithms to stand in for people. Instead, machine intelligence should work together with human intuition to unlock the best possible decision-making for people of all skill levels. In this latest Data Science Central webinar, experts from Qlik will share the latest AI-powered capabilities that enable both user-driven analytics and the democratization of data science. Attendees will get a first-hand look at: How AI accelerates value for all users by suggesting insights, automating tasks and supporting natural language interaction How organizations can deliver the power of data science and predictive models to business decision-makers in a simple, interactive way Demonstrations featuring Qlik’s augmented analytics capabilities, powered by our unique Associative and Cognitive Engines Featured Speakers: Chris Mabardy, Senior Director of Product Marketing -- Qlik Steven Pressland, Senior Product Manager of Augmented Intelligence -- Qlik Hosted by: Sean Welch, Host & Producer -- Data Science Central   Title:  Augmented Analytics for Today’s Business User Date:  Thursday, May 7th, 2020 Time:  9 AM - 10 AM PDT   Space is limited so please register early: Reserve your Webinar seat now

WEBINAR: A Collaborative Approach to Machine Learning - 6 May 2020

Data Science Central Webinar Series Event

A Collaborative Approach to Machine Learning Join us for this latest DSC Webinar on May 6th, 2020 It's generally accepted that you need a team with a wide variety of skills to build modern machine learning (ML) pipelines and make them operational. But what does that team look like, and how do they work together? These questions are especially important when the skills required are particularly specialized. When you’re developing interactive clinical and healthcare applications (backed by specialized statistical methods and made to scale on terabytes of highly complex data), you want the right people by your side. In this latest Data Science Central webinar, we'll describe 3 healthcare and life sciences projects in which business analysts, data scientists, and ML engineers collaborated. These applications and use cases are not only focused on healthcare but across a number of industries. Tune in to learn about the latest advances in big data analytics and artificial intelligence (AI) from PerkinElmer. And see real-life examples of how TIBCO data science and analytics solutions combined with the PerkinElmer AI platform can be used to create: An imaging-based phenotypic screening of cell-based disease models using high-content screening (HCS) Clinical Translational system designed to detect and score significant biomarkers in clinical prognostication Also, find out how, in just three days, a diverse team from TIBCO responded to a critical healthcare, analyzing health outcomes using socioeconomic data from countries around the world. Featured Speakers: Alberto Pascual, Sr. Manager of AI and Analytics Innovation -- PerkinElmer, Inc. Steven Hillion, Sr. Director of Data Science -- TIBCO Software, Inc. Hosted by: Sean Welch, Host and Producer -- Data Science Central   Title:  A Collaborative Approach to Machine Learning Date:  Wednesday, May 6th, 2020 Time:  9:00 AM - 10:00 AM PDT   Space is limited so please register early: Reserve your Webinar seat now

Federated Learning: An Introduction by @_mwitiderrick via @fritzlabs

Improving machine learning models and making them more secure by training on decentralized data.

This is really interesting and I think gives us a clear explanation that we should all be able to follow.

WEBINAR: Mapping Challenges for Self-Service Analytics - 5th May 2020

Data Science Central Webinar Series Event

Mapping Challenges for Self-Service Analytics Join us for this latest DSC Webinar on May 5th, 2020 There are many tools designed to make mapping easy for anyone who wants to explore, analyze, and communicate the spatial patterns in their data. In designing these tools, users experience both the benefits and limitations of systems that are designed to be easy to use and general-purpose, rather than the more complex systems that can be custom designed for any specific user's need. In this latest Data Science Central webinar, Research Scientist Sarah Battersby will address some of the technical design and analytics challenges such as technical base map data, map projections, and distortion. She will also discuss the broader challenges of how people think about maps and how/why these maps will always be just a little bit—or maybe a lot—wrong. Attend and learn how to help people visualize and use spatial information more effectively. Speaker: Sarah Battersby, Research Scientist -- Tableau Hosted by: Sean Welch, Host and Producer -- Data Science Central Title:  Mapping Challenges for Self-Service Analytics Date:  Tuesday, May 5th, 2020 Time:  9:00 AM - 10:00 AM PDT Space is limited so please register early: Reserve your Webinar seat now

Similarity and Distance Metrics for Data Science and Machine Learning by Gonzalo Ferreiro Volpi via @Medium

As applied in Recommendation Systems.

I found this really interesting and it includes the mathematical formulae and some code so you can relate it to your own world.

4 free maths courses to do in quarantine and level up your Data Science skills by Gonzalo Ferreiro Volpi vi\ @TDataScience

Cause there’s no science in data without maths.

A really useful list of free maths courses to do while you have free time. I will freely admit my own maths skills were not good enough and I had to do one myself.  I had always struggled with all the complex formulas that need to be understood.

WEBINAR: Democratizing Analytics from the Ground Up 28 April 2020

Data Science Central Webinar Series Event

Democratizing Analytics from the Ground Up Join us for the latest DSC Webinar on April 28th, 2020 How can you transition your business users from a manual, slow, and prone to error data transformation process in Excel into a scalable and governed solution leveraging a centralized data lake and change the way your employees access and use data? In this latest Data Science Central webinar you will learn how to: Empower self-service data analysis for all of your employees to use Data Prep and Data Studio Transition from a process that heavily relies on siloed Excel work to a Bring Your Own Data (BYOD) approach leveraging a centralized data lake Improve data governance and inspire business and IT collaboration with a single consistent approach to data preparation Accelerate analytics project delivery from months down to weeks Featured Speakers: Christopher Dean, Head of Data, Business Intelligence & Analytics -- Travis Perkins Bertrand Cariou, Sr. Director Product -- Trifacta Hosted by: Rafael Knuth, Contributing Editor -- Data Science Central   Title:  Democratizing Analytics from the Ground Up Date:  Tuesday, April 28th, 2020 Time:  9 AM - 10 AM PDT   Space is limited so please register early: Reserve your Webinar seat now

Top 10 Magic Commands in Python to Boost your Productivity by Siddhesh Jadhav via @TDataScience

Implementation of important IPython magic commands in jupyter notebook.

Very useful and worth a bookmark or save in a file.

Machine Learning and Data Science free online courses to do in quarantine by Gonzalo Ferreiro Volpi via @TDataScience

From beginner to advanced. Get the most of the covid19-lockdown

Some great ideas on how you can stop yourself from being bored as well as do some self-improvement at the same time. I've done some of the free courses on Coursera and they tend to be really good and you learn a lot.

WEBINAR: How to Create Mathematical Optimization Models with Python - 29 April 2020

Data Science Central Webinar Series Event

How to Create Mathematical Optimization Models with Python Join us for the latest DSC Webinar on April 29th, 2020 With mathematical optimization, companies can capture the key features of their business problems in an optimization model and can generate optimal solutions (which are used as the basis to make optimal decisions). Data scientists with some basic mathematical programming skills can easily learn how to build, implement, and maintain mathematical optimization applications. The Gurobi Python API borrows ideas from modeling languages, enabling users to deploy and solve mathematical optimization models with scripts that are easy to write, read, and maintain. Such modules can even be embedded in decision support systems for production-ready applications. In this latest Data Science Central webinar, we will: Discuss the motivation for using Python in mathematical optimization applications Help you understand the importance of parameterizing a mathematical optimization model Review some of the best practices for deploying mathematical optimization models in Python Speaker: Juan Antonio Orozco, Optimization Support Engineer -- Gurobi Optimization Hosted by: Sean Welch, Host and Producer -- Data Science Central Title:  How to Create Mathematical Optimization Models with Python Date:  Wednesday, April 29th, 2020 Time:  9 AM - 10 AM PDT Space is limited so please register early: Reserve your Webinar seat now

5 Premium Courses You Can Access For Free This Month by Liana Mehrabyan via @TDataScience

Udacity offers one month of a premium degree for free, supporting Covid-19 crisis.

Something to stop yourself from being bored as well as keeping your brain active.  I recommend doing something constructive with your time.

Why Python is not the programming language of the future by @RheaMoutafis via @TDataScience

Even though it will be in high demand for a few more years yet.

Something to think about if you are wondering what else to learn.

24 Best (and Free) Books To Understand Machine Learning by Reashikaa Verma via @kdnuggets

KD Nuggets have compiled a list of some of the best (and free) machine learning books that will prove helpful for everyone aspiring to build a career in the field.

I great list of books that could be a useful use of time while you are in isolation.