I really like the simple explanation of heavy machinery behind SVM. Talking Machines: Hosts Katherine Gorman and Neil Lawrence talk about machine learning and … In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications.... Sök Sök Hem Poddar Topplistan Hem Poddar Topplistan Sök Sök Hem Poddar Linear Digressions Spara Hem Poddar Linear Digressions … This weekly podcast also breaks down complex data science problems into digestible chunks that can be appreciated by casual listeners. Every weekday, after yoga and meditation, and before my 10 a.m. stand-up, I dedicate an hour to read while having my first cup of coffee. Linear Digression is a podcast about machine learning and data science… open.spotify.com. Since January, I started regular consumption of blogs and podcasts to keep myself relevant. Linear Digressions is a podcast about machine learning and data science. Although this discipline is based around making smart predictions, many applications of machine learning have been far from predictable. Linear Digressions. Linear Digressions — Ben Jaffe and Katie Malone. Linear Digressions. In each episode (238 in total) of linear digressions, ... Lex Fridman that hosts this podcast is one of the best AI and data science speakers out there. Linear Digressions. (4) A Lot. By the way, Data and AI are two separate newsletters. This episode gets into the story behind that paper: how the approval prospects of different drugs inform the investment decisions of … Linear Digressions Episodes; Contact; So long, and thanks for all the fish. This is a cross-disciplinary study of ‘digression’ as a social-scientific concept. But I didn’t know enough about pairing wine with food to be very effective at knowing … Linear Digressions. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago. Machine learning means looking for patterns in large datasets with statistical and computational methods, and then making predictions or solving problems. Of course, the target audience is merely a recommendation and reading time is heavily dependent on how many links you click and how far down the rabbit hole you go. These articles are well-researched and have cool graphs and fun statistics to quote on. Find out Linear Digressions alternatives. The hosts, Ben Jaffe and Katie Malone, manage to break down complex data science problems and techniques into snippets of information that can be easily digested by the casual listener. I listen to podcasts when I get ready in the morning or when I cook dinner at night. I find KDNuggets to be a good starting point for data scientists who are just beginning their careers or people who are looking to get into data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago. Total Number of Episodes: 164 I also find this newsletter includes more data engineering and ML deployment types of articles. Linear Digressions: Weekly discussion of big data and machine learning. Created and Developed by Renee Marie Parilak Teate, Advanced Beginner - was new to this topic / had some prerequisites, Early Beginner - was totally new to this topic / had few prerequisites. Linear Digressions is a podcast about machine learning and data science. Join us for the inaugural symposium presented by DANG!, the Collaborative Data Science Symposium, a one-day event for data science practitioners of all experience levels in the University of Michigan community.. In this episode, Katie and Ben explain what is the kernel trick in Support Vector Machines (SVM). Read unlimited* books and audiobooks on the web, iPad, iPhone and Android. JUL 26, 2020; So long, and thanks for all … Hosted by Katie Malone and Ben Jaffe, this weekly podcast covers diverse topics in data science and machine learning: talking … Each episode clocks in at around … Co-host GeekSpeak, a semi-weekly radio show and podcast about science and technology. Linear Digressions is a podcast about machine learning and data science. Feature Importance from Linear Digressions on Podchaser, aired Monday, 27th March 2017. 66. Marketplace is your liaison between economics and life. Average episode duration: 15 minutes. K Nearest Neighbors. This provides cities with sources of real-time information that is happening throughout the day in a … Not So Standard Deviations: Really enjoy the data-analysis-as-software-development slant that this podcast always champions. Here are a few interesting podcasts: The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Artificial Intelligence (AI Podcast) with … I do find the recommendation skewed towards articles behind the paid wall though. Which makes sense, because it is wicked cool. The show covers a bit about everything: data science, machine learning, model interpretability, career trajectory, etc. Write a review about lineardigressions.com to share your experience. Linear Digressions. Linear Digressions logo from SoundCloud. United States 291 episodes since Nov. 16, 2014 episodic IN THIS PODCAST digressions Linear Digressions Ben Jaffe … In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications. Host Kai Ryssdal and our team of reporters bring you clear explorations of how economic news affects you, through stories, conversations, newsworthy numbers and more. Katie Malone and Ben Jaffe host Linear Digressions, a weekly podcast that explores recent developments in data science, machine learning, and artificial intelligence. The presenters are entertaining and informative, the topics are always interesting, and the production quality is excellent. Linear Digressions covers the messiest of topics in the field of data science, machine learning and artificial intelligence. Linear digression is all about ML and Data Science, and centers on how ML is solving a multitude of issues around the world, and achieve massive breakthroughs deemed impossible before. On one hand, the algorithm itself is as straightforward as possible: find the labeled points nearest the point that you need to predict, and make a prediction that’s the average of their answers. Data Sci Guide Content Added Dec 2015 – Dec 2016, Multithreaded (stitchfix technology blog), Doing Data Science: Straight Talk from the Frontline, Test and Code – A Podcast about Software Testing, Software Development, and Python, R for Marketing Research and Analytics (Use R! Future of Life Institute: Weekly podcast about everything that could go wrong….very wrong. Not everything in this charming series is directly related to healthcare, but it consistently offers a thoughtful perspective on data and its impact today. Block 1: Big Data and its Discontents. Linear Digressions "In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications." each episode of this podcast has a striking conversation with Elon musk about data science and artificial intelligence. The show covers a bit about everything: data science, machine learning, model interpretability, career trajectory, etc. Linear Digressions; Partially Derivative; Podcast hosts explain complex ideas in a simple way because no one would understand them otherwise When there is an interesting idea presented that I don’t know much about, I take note and google it later. It’s helped us accomplish goals that were out of reach even a few years ago.”. Hunting for the Higgs from Linear Digressions on Podchaser, aired Sunday, 16th November 2014. Listen on Apple Podcasts. In our attempt to round up the best data science podcasts out there, we cast a wide net. Feel free to comment below and let me know! They both often cover AI, Machine Learning, Deep Learning, convex and non-convex optimization, and data engineering. ⭐ What I like about it: you can customize what you read quite easily, and it has a wide variety of content. Linear Digressions. Listen to Linear Digressions on Spotify. This, in turn, increases my confidence to contribute to different AI-related discussions. Word2Vec is probably the go-to algorithm for vectorizing text data these days. It aims to publish contents that help to define and shape data science as a scientifically rigorous and globally impactful multidisciplinary field based on the principled and purposed production, processing, parsing and analysis of data. Figuring out what features actually matter in a model is harder to figure out than you might first guess. This newsletter is split into featured articles, events/webinars, news, tutorials, and opinion pieces. Advanced Beginner - was new to this topic / had some prerequisites, How much did/do you personally learn/gain from this content? This episode features Prof. Andrew Lo, the author of a paper that we discussed recently on Linear Digressions, in which Prof. All good things must come to an end, including this podcast. I get updates on Project Jupyter through the Jupyter Blog, and I first found out about Streamlit on Medium. Seize the opportunity when no manager is constantly lurking behind you and watching your screen. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago. Ratings & Reviews See all » ☆ ☆ ☆ ☆ ☆ 4.8 stars from 508 ratings. Feel free to comment below and let me know! July 26, 2020. The hosts are good friends, and their rapport makes each episode very accessible and easy to understand. Linear Digressions. Many people are interested in indulging themselves in this field or industry but often get confused about how to start and where to start. Each week on Linear Digression, the hosts either discuss a paper related to machine learning or interview someone interesting in the field. Early Beginner - was totally new to this topic / had few prerequisites. Python In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications. Marketplace programs are heard by more than 14 million weekly listeners. ⭐ What I like about it: Occasionally, I don’t understand how it is related, but I get reports from the likes of DataRobot, Gartner, and Figure8 in my inbox through KDNuggets. 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