In this keynote, we announced the launch of Databricks Machine Learning, the first enterprise ML solution that is data-native, collaborative, and supports the full ML lifecycle. This launch introduces a new purpose-built product surface Databricks ML provides a solution for the full ML lifecycle by supporting any data type at any scale, enabling users to train ML models with the ML framework of their choice and managing the model deployment lifecycle – from large scale batch scoring to low latency online serving. Additionally, we announced two machine learning capabilities. First, Databricks Feature Store, the first feature store codesigned with a data and MLOps platform. Second, Databricks AutoML, a ‘glass box’ approach to autoML that accelerates model development without sacrificing control and transparency. Finally, this keynote covers and end-to-end demo of Databricks Machine Learning. Register for free to see the rest of the keynotes and exciting announcements live, plus over 200+ sessions. Learn from the creators and top contributors of technologies like PyTorch, TensorFlow, MLflow, Delta Lake, Apache Spark, Hugging Face, DBT and more. https://databricks.com/dataaisummit/north-america-2021 Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc/
Here we talk about the future role of layers, how their job will change, and how they can best prepare for the 4th industrial revolution.
You are a HUGE football fan. Every week you pick winners in an NFL pick-em’ league. Somehow, all that fan experience doesn’t translate into consistently winning your league. Perhaps you need a more systematic approach that takes some of the emotion out of it. Where to start? Betting spreads provide a consistent and robust mechanism for encapsulating the variables and predicting outcomes of NFL games. In a weekly confidence pool, spreads also perform very well as opposed to intuition-based guessing and “knowledge” from years of being a fan. Can we do better? In this talk, we will discuss an approach to use machine learning algorithms to make improvements on the spread method of ranking winners on a weekly basis as an exercise in winning your friendly neighborhood confidence pool. https://datadialogs.ischool.berkeley.edu/2016/schedule/using-machine-learning-predicting-nfl-games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amit Bhattacharyya Senior Data Scientist Teachers Pay Teachers Amit is the Senior Data Scientist at Teachers Pay Teachers, an online marketplace for teachers to buy, sell and share original educational resources. At TpT, Amit works on developing both technical and modeling infrastructure to analyze customer behavior and ways to more effectively connect buyers and sellers. Amit also teaches in the MIDS program at the UC Berkeley School of Information. He received a Ph.D. in physics from Indiana Universtiy. Previously, he did a two-year stint in advertising, and worked as a quantitative [More]
Wish to build your career in Data Science and Artificial Intelligence space? Here is a video with the best advice from subject matter experts. Listen to these data scientists share tips on how to crack a data science interview or an artificial intelligence interview along with advice on how to make a career transition into AI, Machine Learning and Data Science. You will also find tips on how to build an effective resume. 0:33 AI Career Advice from Swiggy Data Scientist 2:12 Data Science Career Advice from Youplus Data Scientist 3:35 Data Science Career Advice from Flipkart Data Scientist 4:38 DS and AI Career Advice from K-Mart Data Scientist 6:09 Data Science Career Advice from Walmart Labs Data Scientist Subscribe to our channel to get updates on the latest videos. Hit the subscribe button now! http://bit.ly/36DfiCy Who is data science for? http://bit.ly/33M0a2T What are the required skills for data science? http://bit.ly/2qnTFFY What does Machine Learning Engineer do? http://bit.ly/2Yeewry Who are we? Springboard is an online learning platform that helps you master in-demand skills through a personal 1:1 mentor-led model and a project-driven curriculum. Over the last 6+ years, we have served 10K+ learners in 100+ countries. We are now in India and are offering Career Track programs in Data Science, Data Analytics and AI/ML along with job guarantee. Apply here: http://bit.ly/34JJt9D For more information, please write to us at firstname.lastname@example.org or call us at +91 8098866488 or +91 7483024694 Follow Springboard: Facebook: https://www.facebook.com/springboardind/ LinkedIn: https://www.linkedin.com/company/spri Twitter: https://twitter.com/springboard_ind Medium: https://medium.com/@springboard_ind #DataScience [More]
Watch Rachel Thomas’s talk, “How to Learn Deep Learning (When You’re Not a Computer Science PhD)” from the free, live online Demystifying Data Science conference hosted by Metis on September 27, 2017. Rachel Thomas has a math Ph.D. from Duke and was selected by Forbes as one of “20 Incredible Women Advancing AI Research”. She is co-founder of fast.ai and a researcher-in-residence at the University of San Francisco Data Institute. Her background includes working as a quant in energy trading, a data scientist + backend engineer at Uber, and a full-stack software instructor at Hackbright.
👉 Download Our Free Data Science Career Guide:✅https://bit.ly/31XjqMw 👉 Sign up for Our Complete Data Science Training:✅https://bit.ly/3mqEBzW So, you want to become a data scientist? Great! Our free step by step guide will walk you through how to start a career in data science: https://bit.ly/31XjqMw ** Expand for some additional INFO and LINKS ** Data science consulting companies are a hot choice if you’re looking for a job in the field. They offer numerous development opportunities, access to the latest technologies, and provide data-based solutions for top-notch companies across the globe. Furthermore, on top of generous salaries, they seem to have tons of cool perks – from unlimited vacation days and free meals to hair salons and masseuses on site. This doesn’t make your choice any simpler, though. With so many industries and companies out there, it’s hard to keep track of who-offers-what-and-where. So, watch this video to find out which companies provide the best overall employee experience! Complete Data Science Online Training Program. Earn a data science degree at your own pace. Sign up here: https://bit.ly/3mqEBzW Follow us on YouTube: ✅https://www.youtube.com/c/365DataScience Connect with us on our social media platforms: ✅Website: http://bit.ly/2TNHi0B ✅Facebook: https://www.facebook.com/365datascience ✅Instagram: https://www.instagram.com/365datascience ✅Q&A Hub: https://365datascience.com/qa-hub/ ✅LinkedIn: https://www.linkedin.com/company/365datascience Prepare yourself for a career in data science with our comprehensive program: ✅https://bit.ly/3mqEBzW Get in touch about the training at: email@example.com Comment, like, share, and subscribe! We will be happy to hear from you and will get back to you! #data #science #companies #career #firms #scientist
This tutorial was recorded at KDD 2020 as a live, hands-on tutorial. The content is available at https://dssg.github.io/fairness_tutorial/
This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines. – Natural Language Processing (Part 1): Introduction to NLP & Data Science – Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python – Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python – Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python – Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python – Natural Language Processing (Part 6): Text Generation with Markov Chains in Python All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial
In a profound talk about technology and power, author and historian Yuval Noah Harari explains the important difference between fascism and nationalism — and what the consolidation of our data means for the future of democracy. Appearing as a hologram live from Tel Aviv, Harari warns that the greatest danger that now faces liberal democracy is that the revolution in information technology will make dictatorships more efficient and capable of control. “The enemies of liberal democracy hack our feelings of fear and hate and vanity, and then use these feelings to polarize and destroy,” Harari says. “It is the responsibility of all of us to get to know our weaknesses and make sure they don’t become weapons.” (Followed by a brief conversation with TED curator Chris Anderson) Check out more TED Talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Researchers and leaders from academia, hospitals, government and industry gathered for two days at the 2019 Big Data in Precision Health conference at Stanford Medicine to spark collaborations, address challenges, and identify actionable steps for using large-scale data analysis and technology to improve human health. Jeff Dean, PhD, of Google gave a keynote talk. For more information, visit https://bigdata.stanford.edu/
AI With The Best hosted 50+ speakers and hundreds of attendees from all over the world on a single platform on October 14-15, 2017. The platform held live talks, Insights/Questions pages, and bookings for 1-on-1s with speakers. We will discuss multiple ways in which healthcare data is acquired and machine learning methods are currently being introduced into clinical settings. This will include: 1) Modeling disease trends and other predictions, including joint predictions of multiple conditions, from electronic health record (EHR) data using Gaussian processes. 2) Predicting surgical complications and transfer learning methods for combining databases 3) Using mobile apps and integrated sensors for improving the granularity of recorded health data for chronic conditions and 4) The combination of mobile app and social network information in order to predict the spread of contagious disease. Current work in these areas will be presented and the future of machine learning contributions to the field will be discussed. http://withthebest.com/ https://twitter.com/WithTheBest https://www.facebook.com/WithTheBestConf
Katherine Heller, Duke University Computational Challenges in Machine Learning https://simons.berkeley.edu/talks/katherine-heller-2017-5-3
Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.
Talk by Ekaterina Kochmar, University of Cambridge, at the Cambridge Coding Academy Data Science Bootcamp: https://cambridgecoding.com/datascience-bootcamp
Details Dr. Joanna Bryson is professor at Hertie School in Berlin. She works on Artificial Intelligence, ethics and collaborative cognition. She will join us at this edition of the London Ethics Meetup to share her insights on AI, Data & Ethics in 2020. Prof. Joanna Bryson’s current research includes accountability for and transparency in AI; understanding cultural variation in and technological impact on human cooperation, including economic and political behaviour; national and transnational governance of digital technology, the political economy of information communication technology (ICT). https://en.wikipedia.org/wiki/Joanna_Bryson https://www.hertie-school.org/en/research/faculty-and-researchers/profile/person/bryson
Data Science and Artificial Intelligence, are the two most important technologies in the world today. While Data Science makes use of Artificial Intelligence in its operations, it does not completely represent AI. In this article, we will understand the concept of Data Science vs Artificial Intelligence. Furthermore, we will discuss how researchers around the world are shaping modern Artificial Intelligence. What is Data Science? Data Science is the current reigning technology that has conquered industries around the world. It has brought about a fourth industrial revolution in the world today. This a result of the contribution by the massive explosion in data and the growing need of the industries to rely on data to create better products. We have become a part of a data-driven society. Data has become a dire need for industries that need data to make careful decisions. What is Artificial Intelligence? Artificial Intelligence is the intelligence that is possessed by the machines. It is modeled after the natural intelligence that is possessed by animals and humans. Artificial Intelligence makes the use of algorithms to perform autonomous actions. These autonomous actions are similar to the ones performed in the past which were successful. How is Artificial Intelligence Different from Data Science? Let’s start exploring Data Science vs Artificial Intelligence through the below points – 1. Constraints of Contemporary AI Artificial Intelligence and Data Science can use interchangeably. But there are certain differences between the two fields. The contemporary AI used in the world today is the ‘Artificial [More]
Title: Data visualization and artificial intelligence: The real time exploration of unstructured big data Abstract: In this talk we explore the limits of data visualization and why we need to use more and more technology from the world of artificial intelligence. Martino shows us some of the innovations in this field. During the presentation the audience can play with three different DataViz: 1) the exploration of news in real-time; 2) the exploration of a large dataset of videos; 3) the analysis of relationships between entities and topics in a specific corpus of data. MORE INFORMATION: https://sa2015.iiasa.ac.at/
Recorded on Mar 24 2016 at GCP NEXT 2016 in San Francisco. Visual effects rendering is a computationally intensive process where one second of screen-time can require thousands of cores and terabytes of frame data. Learn how Academy Award-winning and recognized studios take advantage of cloud economics and Google’s on-demand computing to realize their creative visions and expand this digital medium for storytelling. Speakers: Julia Ferraioli, Google & David Zuckerman, Wix
For More information Please visit https://www.appliedaicourse.com #ArtificialIntelligence,#MachineLearning,#DeepLearning,#DataScience,#NLP,#AI,#ML
While many celebrated efforts in Artificial Intelligence aim at exceeding human performance, the real promise of AI in real-world domains, such as healthcare and law, hinges on developing systems that can successfully support human experts. In this talk, I’ll share several directions of research we are pursuing towards effective human-AI partnership in the open world, including combining the complementary strengths of human and machine reasoning, addressing concerns around trust, transparency and reliability, and using AI to improve human engagement. Ece Kamar is a senior researcher at the Adaptive Systems and Interaction Group at Microsoft Research. She earned her PhD in computer science from Harvard University where she was advised by Prof. Barbara Grosz. Her research spans several subfields of AI, including planning, machine learning, multi-agent systems and human-computer teamwork, and is inspired by real-world applications that can benefit from the complementary abilities of people and AI. She is particularly interested in the impact of AI on society and developing AI systems that are reliable, unbiased, and trustworthy.
RAFAEL is a global leader in all aspects of the Cyberspace environment, New Space technologies, and Intelligence collection and processing. RAFAEL provides governments, law enforcement agencies, and security forces around the world with novel intelligence and cyber defense solutions ‒ overcoming cyber threats and delivering state-of-the-art protection for critical infrastructures and sensitive data. Based on the company’s in-depth expertise, RAFAEL was selected to head Israel’s national Cyber Emergency Response Team (CERT) as well as other national-level projects including protection of Israel’s Central Credit Register (CCR), the Dominican Republic’s Financial Security Operations Center (SOC), and the cyber defense solution for the G20 Summit in Argentina. With unparalleled expertise in Artificial Intelligence (AI) ‒ based on today’s most sophisticated SIGINT, VISINT and Space-related advances ‒ RAFAEL leads the way in the area of AI for cognitive intelligence systems, enabling organizations and governments to achieve and maintain technological superiority, and assisting them with decision-making at the national level.
Documentary about Artificial Intelligence (AI), Big Data, Robots, Robotics, Machine Learning and any more digital economy topics: Forward Thinking – March of the Machines: The show asks how will the AI revolution change the world? Part one features Jeremy Kahn, Bloomberg Tech Reporter, Mike McDonough Global Chief Economist at Bloomberg Intelligence and Gideon Mann, Head of Data Science at Bloombeg, Part Two features Martin Ford, Author of Rise of the Robots. Part Three features how AI could soon be changing healthcare. Forward Thinking: March of the Machines – Episode 1 Stars: Dafydd Rees, Alastair Bates Genres: Documentary | News The future is uncertain and full of challenges. How do we rescue our cities and tackle inequalities? How do we deal with an aging future and bridging the gender gap? It’s time for some forward thinking. FOLLOW US! ✘ Facebook – https://bit.ly/2ZuPeXp ✘ Instagram – https://bit.ly/3imlHGY ✘ Twitter – https://bit.ly/2PEmZkD SUPPORT US! ✘ Membership – https://bit.ly/2FPCTax #AI #robotics #robots COPYRIGHT: All of the films published by us are legally licensed. We have acquired the rights (at least for specific territories) from the rightholders by contract. If you have questions please send an email to: firstname.lastname@example.org, Amogo Networx – The AVOD Channel Network, www.amogo-networx.com.
⭐ Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I’ve been using Kite for a few months and I love it! https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=krishnaik&utm_content=description-only Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join Please do subscribe my other channel too https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06
🔥Free Data Science with Python course: https://www.simplilearn.com/getting-started-data-science-with-python-skillup?utm_campaign=Skillup-DataScience&utm_medium=DescriptionFirstFold&utm_source=youtube This What is Data Science Video will give you an idea of a life of Data Scientist. This Data Science for Beginners video will also explain the steps involved in the Data Science project, roles & salary offered to a Data Scientist. Data Science is basically dealing with unstructured and structured data. Data Science is a field that comprises of everything that is related to data cleansing, preparation, and data analysis. Start learning today’s most in-demand skills for FREE. Visit us at https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=DataScience&utm_medium=Description&utm_source=youtube Choose over 300 in-demand skills and get access to 1000+ hours of video content for FREE in various technologies like Data Science, Cybersecurity, Project Management & Leadership, Digital Marketing, and much more. Below topics are explained in this Data Science tutorial: 0:00 Introduction 0:10 Life of a Data Scientist – Steps in Data Science project – Understanding the business problem – Data acquisition – Data preparation – Exploratory data analysis – Data modeling – Visualization and communication – Deploy & maintenance 3:11 Roles offered to a Data Scientist 3:53 Salary of a Data Scientist To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Download the Data Science career guide to explore and step into the exciting world of data, and follow the path towards your dream career: https://bit.ly/34ZGYRw Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScience #WhatIsDataScience #DataScienceForBeginners #DataScientist #DataScienceTutorial #DataScienceWithPython #DataScienceWithR #DataScienceCourse #BusinessAnalytics #DataScience101 #MachineLearning This Post Graduate Program in Data Analytics, in partnership with Purdue [More]
Robotics, Artificial Intelligence, internet of things, big data analytics, machine learning, distributed ledger and blockchain technology are all disrupting the markets and businesses. The banking and finance sector itself could be disrupted by new entrants and new technology – FinTechs. FinTech companies are businesses that leverage on new technology to create new and better financial services for both consumers and businesses. They are disrupting the way ordinary people manage and use money and these fintech players can either be a threat or a partner with the traditional and established financial institutions. To provide you with a holistic understanding of the impact emerging FinTechs will have on the future of financial services, GIBS in partnership with Strate, brings you the Fintech Innovation Conference. (August 22, 2017)