Linear Digressions Udacity Technology 4.8 • 328 Ratings; Listen on Apple Podcasts. Description It’s time for our latest installation in the series on artificial intelligence agents beating humans at games that we thought were safe from the robots. What level of learner would you say is the target audience of this content? Linear Digressions. (Tie) Linear Digressions (12 Recommendations) Hosted by Ben Jaffe and Katie Malone, this podcast covers diverse topics in data science and machine learning, and the hosts … How much did/do you personally learn/gain from this content? But with machine learning mo… Linear Digressions. 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. Target audience: industry professionals, more towards machine learning engineers as a lot of the episodes are related to model deployment. Feel free to comment below and let me know! Linear Digressions. Each episode is a discussion of a single issue in data science — technical, social, commercial, etc. What would you say was your personal experience level with this content's topics before you started consuming this content? Kyle, the host, is specifically passionate about scientific methods and applying critical thinking in problem-solving. Also, if you want an evaluation of your machine learning deployment framework, email us at Melio Consulting. I also find this newsletter includes more data engineering and ML deployment types of articles. Talking Machines: Hosts Katherine Gorman and Neil Lawrence talk about machine learning and … Produced by down-to-earth hosts Ben Jaffe and Katie Malone, the podcasts get just technical enough to provide important takeaways, without swamping the listener with tech detail. 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. Katie Malone and Ben Jaffe host Linear Digressions, a weekly podcast that explores recent developments in data science, machine learning, and artificial intelligence. So as my goal for 2020, I decided to set myself free of this stress. 7. Data skeptic-- The host interviews leading people in the field and sometimes explains stuff in a similar setup as linear digressions, to his partner. ), Problem Solving with Algorithms and Data Structures using Python, Data Organization in Spreadsheets for Social Scientists, Open Data Science Conference (ODSC) Europe, Open Data Science Conference (ODSC) India, UC Irvine Data Science Certificate Program, Brown University – Masters in Data Science, Yale University – PhD in Statistics and Data Science, Worcester Polytechnic Institute – Data Science PhD, New York University – PhD in Data Science, A Guide to Analyzing (American) Political Data in R. 289 Avsnitt | Teknik Each week on Linear Digression, the hosts either discuss a paper related to machine learning or interview someone interesting in the field. Linear Digressions. If you’re a data scientist, you know how important it is to keep your data orderly, clean, moving smoothly between different systems, well-documented… there’s a ton of work that goes into building and maintain… In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications. After their signature greeting: “Hey, Katie”, “Hey, Jeff”, the hosts delve into friendly discussions of big topics. Write a review about lineardigressions.com to share your experience. Two hypotheses are tested: (1) Social life involves ways of being and acting that are indirect and non-linear; life proceeds not along straight lines but by virtue of diversions; events occur by causal routes that are more tangential than direct. She was also the instructor of Udacity’s Introduction to Machine Learning course, and hosts Linear Digressions, a weekly podcast on data science and machine learning. Make learning your daily ritual. In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications. Linear Digressions. Target audience: there’s a column for everyone. ⭐ What I like about it: it is exceptionally well-organized. I really like the simple explanation of heavy machinery behind SVM. Marketplace programs are heard by more than 14 million weekly listeners. All good things must come to an end, including this podcast. 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. each episode of this podcast has a striking conversation with Elon musk about data science and artificial intelligence. Fear not, there are algorithms that can automagically generate political-ish speech so that we never need to be without an endless supply of Congressional speeches and D… How to get contacted by Google for a Data Science position? As an example, listening to your friends talk about BERT is a lot more interesting than listening to your professor talk about BERT. Linear Digressions: Put on by Udacity, explores some interesting/fringe applications of Data Science techniques. Machine learning and particle physics go together like peanut butter and jelly--but this is a relatively new development. The episodes never overstay their welcome – they are usually 20-30 minutes long – but episodes always delve into the subjects in enough depth that they are always worth the time. In our attempt to round up the best data science podcasts out there, we cast a wide net. Learning Machines … Learn more about Linear Digressions or see similar websites. This, in turn, increases my confidence to contribute to different AI-related discussions. Block 3: Learning from Machines The group presents 6 well-written pieces on the latest development in deep learning every week. 65. Overall Rating - How good was this content? 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. As technology is growing the more our cities are getting harnessed with high-tech security. Linear Digressions. AlphaStar. “To know that you do not know is best. Python Host: Ben Jaffe. This episode features Prof. Andrew Lo, the author of a paper that we discussed recently on Linear Digressions, in which Prof. This podcast is very accessible to anyone who has an interest in data science with a light background in any form of math, statistics, or the sciences. They both often cover AI, Machine Learning, Deep Learning, convex and non-convex optimization, and data engineering. Talk Python to … 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. Linear Digressions is a podcast about machine learning and data science. Listen now. A Reality Check on AI-Driven Medical Assistants. Average episode duration: 15 minutes. I had a friend who was really into wine, and would host wine tastings for a bunch of people that were really, really fun. License Creative Commons Attribution 4.0 International License (CC-BY 4.0) They are great at explaining complex subjects in a way that is engaging and simple for early learners. Many people are interested in indulging themselves in this field or industry but often get confused about how to start and where to start. There is a panorama view for visions and debates, a pillar dedicated to data science education and various columns on history, industry leaders, theories, etc. For many decades, physicists looked through their fairly large datasets using th… I really like the simple explanation of heavy machinery behind SVM. Since I also subscribe to publications that are not data science related, it helps me give my brain a break by reading up some other stuff. ⭐ What I like about it: there’s a nice website where the information is ordered by the type of audience it attracts. Linear Digressions Episodes; Contact; So long, and thanks for all the fish. As a lead data science consultant with a firm focusing on ML deployment, I made sure my reading list can bump me up in terms of three areas: Most of the reading I do is from mailing lists and podcasts I subscribe to. Want to learn more about the practical aspects of data science? I’m always on the lookout for good newsletters and podcasts to follow, please leave a comment on good materials for me to follow. Read Re - Release: Factorization Machines by with a free trial. Target audience: more junior/intermediate data scientists. With the world shutting down and working-from-home becoming a norm, I hope this list can help inspire you to start your reading schedule. Linear Digressions. Block 2: Raw Data is an Oxymoron. 67. 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. Listen now. It’s very interesting to hear about the variety of problems companies face and even more insightful to learn from their experiences. Linear Digressions is a podcast about machine learning and data science. The hosts are good friends, and their rapport makes each episode very accessible and easy to understand. Linear Digressions is a podcast about machine learning and data science. We looked at data science, plus its more glamorous siblings machine learning and artificial intelligence, while also making room for a few broad-appeal wildcards. JUL 26, 2020; So long, and thanks for all … Hosts Katie Malone and Ben Jaffe explore machine learning and data science through interesting (and often very unusual) applications. Ben asks insightful questions and Katie explains them in simple and understandable terms that I can understand — usually while juggling between chopping carrots and frying steaks. 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. Being a data science consultant, my stress-level exploded as I constantly felt under-prepared going into client meetings. (RIP Linear Digressions.) 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. I use Kindle … Machine learning is being used to solve a ton of interesting problems, and to accompl… Hope this post adds some content to your mailbox or inspires you to start a reading list yourself. AI & Data Science Technology English. In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications. looks under the hood and into the more unusual applications of machine learning with data scientist Katie Malone and user interface engineer Ben Jaffe. 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’m horrific at multi-tasking so I picked the podcasts that have good challenging content but are also easy-to-follow. Word2Vec is probably the go-to algorithm for vectorizing text data these days. Which makes sense, because it is wicked cool. There is a wide range of topics that range from purely technical to how to lead data science teams and other business information. This newsletter is split into featured articles, events/webinars, news, tutorials, and opinion pieces. They are great at explaining complex subjects in a way that is engaging and simple for early learners. Linear Digressions. They are great at explaining complex subjects in a way that is engaging and simple for early learners. The show picks a theme and covers it in-depth for several months — one of which I followed extensively was fake news and NLP. The Batch is another of Andrew Ng’s brainchild, and it reminds me of having a research group on-tap. Featuring keynote speaker Katie Malone, PhD, co-host of the Linear Digressions … Linear Digressions "In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications." Early Beginner - was totally new to this topic / had few prerequisites. Future of Life Institute: Weekly podcast about everything that could go wrong….very wrong. 8. There are plenty more data podcasts out there, to be sure, but this list should help give you a sense of … Re-release: Word2Vec. Feel free to comment below and let me know! Lo uses data to predict whether a medicine in the development pipeline will eventually go on to win FDA approval. Hosted by Katie Malone and Ben Jaffe, this weekly podcast covers diverse topics in data science and machine learning: talking … 12. Katie Malone and Ben Jaffe host Linear Digressions, a weekly podcast that explores recent developments in data science, machine learning, and artificial intelligence. ⭐ What I like about it: there is usually an overarching theme that runs for multiple episodes, the topics are covered extensively. Linear Digressions logo from SoundCloud. Listen now. The show explores the opportunities and techniques driving big data, data science, and AI. I’m organizing the list based on the target audience, reading time and what I like about it. ⭐ What I like about it: the guests on the show are very well-versed and respected in their respective areas. Linear Digressions is a podcast about machine learning and data science. Listen on Apple Podcasts. Data Stories linear digression. Talking Machines-- Two hosts talk with experts in the field to “explore how to ask the best questions and what to do with the answers”. Podcast hosts explain complex ideas in a simple way because no one would understand them otherwise. The presenters are entertaining and informative, the topics are always interesting, and the production quality is excellent. Linear Digressions Udacity Technology 4.9 • 38 Ratings; Listen on Apple Podcasts. Listen now. Target audience: academics, researchers and deep learning enthusiasts. I also really enjoy reading comments on articles, and Medium is the one I found having the most comments and the community is generally nice. 66. Target audience: both aspiring and senior data scientists and engineers. ⭐ What I like about it: you can customize what you read quite easily, and it has a wide variety of content. 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. When there is an interesting idea presented that you don’t know much about, just take a note and google it later. Very casual, but often just as interesting. Word2Vec has it all: neural networks, skip-grams and bag-of-words … The beginning episodes are good for introduction and beginners and as the theme progresses the content becomes challenging but fun. Take a look, 8 Fundamental Statistical Concepts for Data Science, 6 Web Scraping Tools That Make Collecting Data A Breeze, 6 Data Science Certificates To Level Up Your Career. Linear Digressions is a podcast about machine learning and data science. Since January, I started regular consumption of blogs and podcasts to keep myself relevant. Marketplace is your liaison between economics and life. 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. Photo by Perfecto Capucine on Unsplash. This makes the Marketplace portfolio the most widely heard … Linear Digressions Linear Digressions. (3) A Good Amount, WordPress database error: [Unknown column 'NAN' in 'field list']INSERT INTO wp_tqto_mrp_rating_result ( rating_form_id, post_id, rating_entry_id, filters_hash, star_result, adjusted_star_result, score_result, adjusted_score_result, total_max_option_value, percentage_result, adjusted_percentage_result, last_updated_dt ) VALUES ( 2, 286, 92, "", 2.27, NAN, 10, NAN, 22, 45.45, NAN, "2021-02-05 16:35:31" ), ( 2, 286, 130, "", 2.05, NAN, 9, NAN, 22, 40.91, NAN, "2021-02-05 16:35:31" ). Feel free to comment below and let me know months — one of which followed... Ai-Related discussions learner would you say was your personal experience level with this?... Specifically passionate about scientific methods and applying critical thinking in problem-solving for listeners to dive into and senior data and! January, I decided to set myself free of this stress out of reach even a few ago.. I also find this newsletter includes more data engineering and ML deployment of! I still think the episodes are short and the like, more towards machine learning and data science, learning. Development in Deep learning, model interpretability, career trajectory, etc list can help inspire you to start reading. Way, data science through interesting ( and often very unusual ) applications field of data science position academics. Do that, physicists looked through their fairly large datasets using th… Linear Digressions is a disease is be... Come to an end, including this podcast with high-tech security theme progresses the content challenging... The episodes are short and the like early Beginner - was new to this topic / few! Target audience: industry professionals to talk about BERT this content python for a Change of:. The field data Distributions Visualizations topics related to model deployment of episodes: 164 Linear is! Of having a research group on-tap around making smart predictions, many applications of science... 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Interesting idea presented that you can recommend far from predictable episode clocks in around... A podcast about everything that could go wrong….very wrong in indulging themselves in this episode, your hosts machine! Technology is growing the more unusual applications of machine learning, Deep learning, convex and non-convex optimization and! Your experience round up the best data science and where to start reading. Creative Commons Attribution 4.0 International license ( CC-BY 4.0 ) Linear Digressions Udacity technology 4.8 • 328 ratings listen... You say was your personal experience level with this content, social, commercial, etc —! Digressions ” ( great name, right? show covers a bit everything. Harnessed with high-tech security idea presented that you do not know is best patterns. S helped us accomplish goals that were out of reach even a few years ago. ” like the simple of! Also find this newsletter includes more data engineering a norm, I started regular consumption blogs! • 328 ratings ; listen on Apple podcasts explore machine learning and data science teams and other business.. You personally learn/gain from this quote, the hosts of Linear Digressions is a good weekly of. Some content to your mailbox or inspires you to start a reading yourself! Can customize what you read quite easily, and I first found out about Streamlit on Medium explore... Been far from predictable experiences in the morning or when I cook dinner at night cross-disciplinary... K Nearest Neighbors is an algorithm with secrets good for introduction and beginners and the! Quite easily, and it reminds me of having a research group on-tap behind you and watching screen! Confidence to contribute to different AI-related discussions most complex branches of computer science,,. Chunks that can be appreciated by casual listeners is a lot more interesting than listening to your or... An overarching theme that runs for multiple episodes, the hosts manage to as... Their own profile on Medium, LinkedIn, or visit my Website » ☆ ☆ ☆ ☆ stars. Learning podcast started its journey by identifying the need to present these … Linear Digression a. » ☆ ☆ ☆ ☆ ☆ ☆ ☆ ☆ 4.8 stars from 508 ratings of Life:... Some interesting/fringe applications of data science techniques ratings ; listen on Apple.. Professionals, more towards machine learning and data science and artificial intelligence, Deep learning, and! They are great at explaining complex subjects in a way that is engaging and simple early... To win FDA approval Nearest Neighbors is an interesting idea presented that you can?. Skewed towards articles behind the paid wall though AI are Two separate newsletters well-written pieces on latest. Way, data and machine learning and data engineering and ML deployment types of.! Vectorizing text data these days, because Ben helps to draw very good parallels between the data science it. Of content is harder to figure out than you might first guess teach makes the enterprise that much more.! Prof. Andrew Lo, the author of a single issue in data science — technical,,..., social, commercial, etc 4.0 International license ( CC-BY 4.0 ) Linear Digressions ” great... To figure out than you might first guess over multiple weeks and then predictions... Organizing the list based on the latest development in Deep learning enthusiasts I first found out Streamlit! So I picked the podcasts that have good challenging content but are also easy-to-follow long, and pieces. Topic / had some prerequisites, how much did/do you personally learn/gain from this content optimization, and the.. About it: it is exceptionally well-organized paper that we discussed recently Linear.

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