MIT 6.0002 11. Introduction to Machine Learning
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MIT 6.0002 11. Introduction to Machine Learning

MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016View the complete course: http://ocw.mit.edu/6-0002F16Instructor: Eric Grimson In this lecture, Prof. Grimson introduces machine learning and shows examples of supervised learning using feature vectors. License: Creative Commons BY-NC-SAMore information at http://ocw.mit.edu/termsMore courses at http://ocw.mit.edu
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What does a head of data science look for in a junior? | Interview with Ken Jee

Ken Jee is the head of data science at Scouts Consulting, a data science team which helps sports teams and athletes improve their performance based on data. He also makes YouTube videos answering many of the questions junior data scientists have. Links: Ken’s channel – https://www.youtube.com/channel/UCiT9RITQ9PW6BhXK0y2jaeg Ken interviewing me – https://youtu.be/hO_YKK_0Qck Article version of Ken […]
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How To Become A Data scientist Part 1 – It's the science!

Since data science is all the rage these days, people often wonder how they can transition from their current career into data science. I think one of the most important things to keep in mind when planning your career change is to really focus on the science. Learn how to be a good scientist, how […]
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DeepLearning.AI Learner Community Event ft. Ghaith Sankari

deeplearning.ai presents virtual mini-event series for our Learner Community of those taking the AI for Medicine specialization! #MeetYourMentor: Mentors sharing their personal experiences of breaking into AI #DeepDive: A deep dive into a specific area that the guest speaker is working on and more! This event will be from 10am to 10:30 am on May […]
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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/ […]
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5 Beginner Friendly Steps to Learn Machine Learning

This video breaks down practical steps on how to learning machine learning with Python. It’s the video I wish I had watched when I started learning machine learning. My machine learning course – https://dbourke.link/mlcourse Blog post version of this video – https://dbourke.link/5stepstoml Learn all of this in one place on DataCamp – http://bit.ly/datacampmrdbourke Bonus: A […]
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Zero to Mastery Machine Learning Course Launch! | Ask me anything! (live)

One of my good friends Andrei Neagoie and I just launched a massive data science and machine learning course on Udemy! Since I’m one-half of the instructors, I’ll be saying hello and answering any questions about the course you might have. Check out the course – https://dbourke.link/mlcourse (there’s a link down the bottom to the […]
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Study with me: Data Science (25-minute session)

Studying can be tough. But you’re not alone. I use the pomodoro technique (25-minutes of concentrated work, then a 5-minute break) every day. More on the technique – https://en.wikipedia.org/wiki/Pomodoro_Technique CONNECT: Web – http://bit.ly/mrdbourkeweb Quora – http://bit.ly/mrdbourkequora Medium – http://bit.ly/mrdbourkemedium Twitter – http://bit.ly/mrdbourketwitter LinkedIn – http://bit.ly/mrdbourkelinkedin Email updates – http://bit.ly/mrdbourkenewsletter #datascience #studywithme #machinelearning Source of this […]
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The Tools that I use for Data Science and Machine Learning

I use a variety of tools for my data science and machine learning. I started out in IT, so my toolset tends to be software developer heavy. I use VSCode as my IDE of choice for just about anything that supports it. I also use Jupyter and lately JupyterLab. For the full set, check out […]
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How to learn data science with Coursera in 2022 (beginner-friendly)

This video details how to create your own beginner-friendly curriculum using Notion to learn Python, data science and machine learning on Coursera in 2022. Get $100USD off Coursera Plus yearly (before Jan 13) – https://dbourke.link/coursera-plus-2022-deal Notion data science curriculum template – https://dbourke.link/coursera-notion-template-2022 Note: some links are affiliate links which means if you click one and […]
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How to Create Your Own Data Science Curriculum with Coursera in 2021

If you’re looking to learn data science in 2021, perhaps you might be interested in creating your own self-guided, self-paced curriculum. This video shows how you might create one using Coursera and Notion. Sign up to Coursera Plus – https://dbourke.link/courseraplus Coursera Data Science Curriculum Notion Template – https://dbourke.link/coursera-notion-template Blog post version of this video – […]
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Industrializing Machine Learning at Shell with Daniel Jeavons – TWiML Talk #202

In this episode of our AI Platforms series, we’re joined by Daniel Jeavons, General Manager of Data Science at Shell. In our conversation, Daniel and I explore the evolution of analytics and data science at Shell, and cover a ton of interesting machine learning use cases that the company is pursuing, such as well drilling […]
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HAPPY NEW YEAR! 4k Subscriber Q&A + My curriculum for 2019

I answered your questions on data science, machine learning, health and everything in between live on stream. If your question wasn’t answered, feel free to email me anytime and ask: daniel@mrdbourke.com Links mentioned in the show: My Self-Created AI Masters Degree – http://bit.ly/AIMastersDegree The Five C’s of Online Learning (article on how to choose an […]
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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 […]
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The 100 Days is Over! | 100 Days of Code 17

What a journey it has been! Here’s to the next 1000 days. Links mentioned in the video: Medium 100 Days of Code Series – https://medium.com/series/my-100-days-of-code-bf23b507fc77 How I’m Learning Deep Learning in 2017 – https://medium.com/@MrDBourke/how-im-learning-deep-learning-in-2017-part-1-632f4187ce4c CS50 (Introduction to Computer Science) – https://www.edx.org/course/introduction-computer-science-harvardx-cs50x Udacity Intro to Data Science – https://www.udacity.com/course/intro-to-data-science–ud359 My GitHub – https://www.github.com/mrdbourke My Self-Create AI […]
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#TWIMLfest: Office Hours – Reinforcement Learning

In the Office Hours series, we invite experts and practitioners in various topic areas for AMA (ask-me-anything) style sessions to answer community member questions. The intent is to answer technical questions and/or help participants advance their specific projects and interests. This week’s topic will be centered on Reinforcement Learning! Resources: Show notebooks in Drive – […]
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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 […]
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T12 16 Panel: Causal ML in industry

Speakers: Greg Lewis, Senior Principal Researcher, Microsoft Research Redmond Ya Xu, Head of Data, LinkedIn Totte Harinen, Data Scientist, Toyota Research Institute Dawen Liang, Senior Research Scientist, Netflix Causal ML is widely used by data science teams in the tech world to give business decision makers data-driven answers. In this panel data science leaders at […]
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Advancing Your Data Science Career During the Pandemic

The global pandemic has impacted us all, changing the career landscape for many, and creating disruption and uncertainty. The US is currently experiencing its worst unemployment rate in nearly a century, and the data science and machine learning communities are no exception. In this discussion, we will explore ways that Data Scientists and ML/AI practitioners […]
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Joan Bruna & Michael Bronstein Interview – Geometric Deep Learning

This week on the podcast we’re featuring a series of conversations from the NIPs conference in Long Beach, California. I attended a bunch of talks and learned a ton, organized an impromptu roundtable on Building AI Products, and met a bunch of great people, including some former TWiML Talk guests. This time around I’m joined […]