Live from TWIMLcon! Scaling ML in the Traditional Enterprise – #309

In this episode from a stellar TWIMLcon panel, the state and future of larger, more established brands is analyzed and discussed. Hear from Amr Awadallah, Founder and Global CTO of Cloudera, Pallav Agrawal, Director of Data Science at Levi Strauss & Co., and Jürgen Weichenberger, Data Science Senior Principal & Global AI Lead at Accenture, […]

AI Enterprise Workflow Study Group – Course 1 Week 2

This is the recording from the second meeting of our AI Enterprise Workflow study group, recorded on Saturday Feb 29th. Week two dove deeper into data ingestion and featured a case study/project that reinforced the principles discussed in the lectures. Specific topics discussed this time include: – Data ingestion – ETL, etc. – Data science […]

Kirk Borne Interview – Towards the Self-Driving Enterprise

In this show, the first of our PegaWorld 18 series, I’m joined by Kirk Borne, Principal Data Scientist at management consulting firm Booz Allen Hamilton. In our conversation, Kirk shares his views on automation as it applies to enterprises and their customers. We discuss his experiences evangelizing data science within the context of a large […]

2030 Vision: Can Data Science Improve Lives of the Disadvantaged? | CogX 2019

Join the CogX Global Leadership Summit and Festival of AI and Breakthroughs Technology – June 8th to 10th 2020 – https://cogx.co/ Subscribe to our epic newsletters for free https://cognitionx.com/newsletter-subscribe/ 2030 Vision: Can Data Science Improve Lives of the Disadvantaged? Presentation given at CogX 2019, on the Future of Work and Education. Tariq Khokhar; Chief Data […]

Do You Dare Run Your ML Experiments in Production? with Ville Tuulos – #523

Today we’re joined by a friend of the show and return guest Ville Tuulos, CEO and co-founder of Outerbounds. In our previous conversations with Ville, we explored his experience building and deploying the open-source framework, Metaflow, while working at Netflix. Since our last chat, Ville has embarked on a few new journeys, including writing the […]

Agile Applied AI Research with Parvez Ahammad – #492

Today we’re joined by Parvez Ahammad, head of data science applied research at LinkedIn. In our conversation, Parvez shares his interesting take on organizing principles for his organization, starting with how data science teams are broadly organized at LinkedIn. We explore how they ensure time investments on long-term projects are managed, how to identify products […]

Case Study: Airbus | CogX 2019

Join the CogX Global Leadership Summit and Festival of AI and Breakthroughs Technology – June 8th to 10th 2020 – https://cogx.co/ Subscribe to our epic newsletters for free https://cognitionx.com/newsletter-subscribe/ Case Study: Airbus. Presentation given at CogX 2019, on the Lab to Live Stage Pete Burnap; Professor of Data Science and Cybersecurity, Cardiff University Matilda Rhode; […]

Topic Modeling for Customer Insights at USAA with William Fehlman – TWIML Talk #276

Today we’re joined by William Fehlman, director of data science at USAA. We caught up with William a while back to discuss: His work on topic modeling, which USAA uses in various scenarios, including chat channels with members via mobile and desktop interfaces. How their datasets are generated. Explored methodologies of topic modeling, including latent […]

The Alan Turing Institute: Data Science for Science | CogX 2020

The Alan Turing Institute: Data Science for Science Ella Gale – Postdoctoral Research Associate – University of Bristol Adrian Bevan – Director – Particle Physics Research Centre Adeniyi Fasoro – Research Project Manager, AI for Science – The Alan Turing Institute Hugh Williamson – Research Fellow – University of Exeter Bringing the world’s most interesting […]

AI for Social Good: Why “Good” isn’t Enough with Ben Green – #368

Today we’re joined by Ben Green, PhD Candidate at Harvard, Affiliate at the Berkman Klein Center for Internet & Society at Harvard, Research Fellow at the AI Now Institute at NYU. Ben’s research is focused on social and policy impacts of data science, with a focus on algorithmic fairness, municipal governments, and the criminal justice […]

#TWIMLfest – AI and ML in Physics: Research, Education, and Career

This session aims to connect and advocate for physicists involved in data science. We will be discussing cutting-edge data science applications in physics research, data science education approaches in the physics curriculum, as well as how physicists with AI/ML experience can transfer their skill sets to careers in industry. We also hope this session can […]

Data Science in 4 Minutes: Quick High Level Overview

In this video I discuss classification, regression, overfitting, underfitting, bias, variance, and feature engineering. This gives a very quick overview of data science in 4 minutes. Source of this machine learning/AI Video

Deep Learning for NLP: From the Trenches with Charlene Chambliss – #433

Today we’re joined by Charlene Chambliss, Machine Learning Engineer at Primer AI.  Charlene, who we also had the pleasure of hosting at NLP Office Hours during TWIMLfest, is back to share some of the work she’s been doing with NLP. In our conversation, we explore her experiences working with newer NLP models and tools like […]

Buy AND Build for Production Machine Learning with Nir Bar-Lev – #488

Today we’re joined by Nir Bar-Lev, co-founder and CEO of ClearML. In our conversation with Nir, we explore how his view of the wide vs deep machine learning platforms paradox has changed and evolved over time, how companies should think about building vs buying and integration, and his thoughts on why experiment management has become […]

50K Subscribers for my Coding Machine Learning Channel

My channel hit 50K subscribers on YouTube!! Thank you everyone for the support and your interest in my channel. In this video I discuss taking a small YouTube channel to 50K and beyond, how I used side projects and social media channels, such as Twitter, GitHub, and Medium. For YouTube I use a Canon M50 […]

Installing the NVIDIA Data Science Stack on Linux with a ThinkPad P53

In this video I show how to install/upgrade the NVIDIA Data Science Stack. This allows management of a data science environment on a Linux desktop (as opposed to command line) system. Data Science Stack: https://github.com/NVIDIA/data-science-stack Dealing with invalid certs: https://github.com/NVIDIA/nvidia-docker/issues/837 Lenovo P-Series: https://www.lenovo.com/us/en/laptops/thinkpad/thinkpad-p/c/thinkpadp ** Follow Me on Social Media! GitHub: https://github.com/jeffheaton Twitter: https://twitter.com/jeffheaton Instagram: https://www.instagram.com/jeffheatondotcom/ […]