Jul 17, 2021 ... r/MachineLearning Current search is within r/MachineLearning. Remove r/MachineLearning filter and expand search to all of Reddit. TRENDING ...569 votes, 81 comments. 387K subscribers in the learnmachinelearning community. A subreddit dedicated to learning machine learningSecondly, learning and education is not a baby feeding session nor is it a quick hit with the golden solution. It is the pursuit of finding answers and solutions wherever they may be and using many different sources, however lengthy (e.g. a book) or a 13-minute YouTube clip (which you can scrub through to the end by the way, where the ...I made the following post on other subs too. Just posting it here to get the input from larger machine learning community. Hi all, I recently completed my research based masters in computer vision and currently working in a company as a computer vision researcher. My current role requires a lot of paper reading to improve the existing models.A linear classifier is the hello world of machine learning. If you're interested in robotics is specifically you'll want to learn Reinforcement Learning which is probably the most difficult area of ML to get into. Unfortunately Reinforcement Learning (RL) falls … The post says "future." - Machine learning is about minimizing loss. In deep learning it propagates this through linear, lstm, and conv layers. - However, the differentiable programming ecosystem will move beyond these rigid confines to minimize loss in any function. r/learnmachinelearning. • 1 yr. ago. DeF_uIt. Is ML career worth it? Firstly I stuck with web backend development because of the huge pool of job openings and high payment. But then I'v got interested in machine learning (Deep learning, RL, CV actually all of that look attractive to me). Machine learning engineer here with no college degree! It is possible but the road is hard. Way harder than if you were to have the education appropriate for said position. I taught myself how to program 3 years ago after getting out of the Army. This was because I too was interested in machine learning and AI.But most of my interest was for the mathematics behind Machine Learning and AI. And most of the ML projects are just programming on keras and stuff. Like there can be maths involved here, just not the heavy kind like we learn in theory, so is there usually much research going on under AI making or refining mathematical algorithms for AI ... I work as a software engineer in machine learning mainly for R&D computer vision models. The day goes: 08 - Check results from model trained overnight, understand them, document. This is a subreddit for machine learning professionals. We share content on practical artificial intelligence: machine learning tutorials, DIY, projects, educative videos, new tools, demos, … Here we go again... Discussion on training model with Apple silicon. "Finally, the 32-core Neural Engine is 40% faster. And M2 Ultra can support an enormous 192GB of unified memory, which is 50% more than M1 Ultra, enabling it to do things other chips just can't do. For example, in a single system, it can train massive ML workloads, like large tra Representing words with words - a logical approach to word embedding using a self-supervised Tsetlin Machine Autoencoder. Hi all! Here is a new self-supervised machine learning approach that captures word meaning with concise logical expressions. The logical expressions consist of contextual words like “black,” “cup,” and “hot” to ... Referenced Symbols. +0.35%. The Federal Trade Commission has launched an inquiry into Reddit’s licensing of user data to artificial-intelligence companies — just days …Jun 7, 2022 ... Reddit, Inc. © 2024. All rights reserved. r/learnmachinelearning. Join. Learn Machine Learning. A subreddit dedicated to learning machine ...The completely new version of Fast.ai 's super popular Practical Deep Learning for Coders course was just put online today. This is the course I recommend the most to people wanting to learn how to create real deep learning models. They've apparently re-written the whole course from the ground up. This is great.CodingGuy47 • 9 mo. ago. It is possible to do so but it's not recommended as the ML tutorials for java are very slim, Java should generally not be used for ML, Not to say that you can't make ML models in java but its abilities are better suited for making mobile applications, web applications, and banking applications, but if you're set on ...NoPlansForNigel. •. AI will always be as good at generating code as you are at describing what you want. Doing a precise description of the software you want has always been the hardest …How strong are the magnets in an MRI machine? Can they pull a watch of your arm or even more? Learn just how strong MRI magnets are on this page. Advertisement The biggest and mos...In those cases, the language choice should not be driven by what language has the most advanced libraries. And my gut feeling is that people rush to Python when in fact for their context (and assuming they already know the Java ecosystem and not so much the Python one) the ROI won't be good. wildjokers. •.If you think that scandalous, mean-spirited or downright bizarre final wills are only things you see in crazy movies, then think again. It turns out that real people who want to ma...Yeah I see. My question is more like, which book would be good for obtaining a solid understanding of the different ML techniques (including mathematical descriptions, algorithmic analysis, exercises with a solutions manual) that could pave the way for a more analytical and mathematical understanding of ML potentially far into the future (like in some parts of …Machine Learning is a very active field of research. The two most prominent conferences are without a doubt NIPS and ICML. Both sites contain the pdf-version of the papers accepted there, they're a great way to catch up on the most up-to-date research in the field. ... This subreddit is temporarily closed in protest of Reddit killing third ...At the company I work at, we've hired candidates who have gone on to be fantastic machine learning researchers without asking them for a GitHub repo or 3 years of Kaggle history. None of that crap. All you need to be successful (and what we look for) is have a solid understanding of the background maths (elements of calculus, linear algebra ...Yes, ML is very much possible to be self taught, with the amount of online blogs and free courses on Coursera, it is very much possible. You can check out the popular Andrew NG's Machine Learning course from Coursera and then move on to deep learning.ai course. Another very detailed and in depth ML course will be from NPTEL.CodingGuy47 • 9 mo. ago. It is possible to do so but it's not recommended as the ML tutorials for java are very slim, Java should generally not be used for ML, Not to say that you can't make ML models in java but its abilities are better suited for making mobile applications, web applications, and banking applications, but if you're set on ... 1)General Python programming. Usually leetcode type questions about implementing something in Python, or questions about Python's features. Also very helpful to know mundane stuff like pulling data from APIs, formatting strings, and so on. 2)General Machine Learning and statistics questions. These tended to be theoretical. In those cases, the language choice should not be driven by what language has the most advanced libraries. And my gut feeling is that people rush to Python when in fact for their context (and assuming they already know the Java ecosystem and not so much the Python one) the ROI won't be good. wildjokers. •.I spent a summer as a Data Scientist intern and now work as ML Engineer. If you enjoy coding more, do ML Engineer. ML Engineer is just a specialized Software Engineer. If you ever seen the role "Software Engineer - Machine Learning" that's pretty much interchangeable with ML Engineer. Most ML Engineers I've met come from having Software ... Machine learning is much broader than this one approach. The crucial distinguishing feature of ML from data science is that machine learning's focus is on methods of learning from data. Unlike data models where the relationships of elements is pre-defined by programmers or architects, machine learning algorithms discover the patterns in the ... Hopefully a masters program will give you some inkling as well. Master's or Ph.D. degrees sound great only if you wanna do in-depth studies. If you really want to learn more, then you should go for it, but remember it is time-consuming. So, rather than, I would suggest you also look for post-graduate courses. Know how ML‘s potential can be utilized to serve themselves (or their teams) resources: coursera – ai for everyone andrew ng – machine learning yearning coursera – machine learning (first …A robust machine learning engineering skill set is hard won, just like compilers, operating systems, or distributed systems skillsets. So while you (perhaps thankfully) don’t have to acquire a PHD, getting into ML engineering isn’t a walk in the park. Presented below is an inevitably incomplete, but still fleshed out list of resources for ... When possible, these guides have stuck closely to the views of established Machine Learning engineers and researchers. In other places, the author has forwards their view of things. Please feel free to submit feedback and improvements for these any parts of these guides. 1. Getting Into ML: High Schoolers Guide. 2. The secret to improving the predictive ability of machine learning is the sometimes deceptively obvious. The answer is feature engineering. You and cardiologist (in this case) need to think about what clues does a human use for making this decision that is not directly available in all the data that you are providing and then transform the data as necessary …Here are our top picks of Reddit’s machine learning datasets. Best Reddit Datasets for Machine Learning. Cryptocurrency Reddit Comments Dataset: Containing …Speaking towards #2, if you want to solve real world problems by applying machine learning (ML) to well-understood domains and build products around that, that sounds more like an ML engineer. If you want to start doing things that push the frontier, merging many techniques from different areas of ML or solving brand new problems with ML, that ...Without further ado, here are my picks for the best machine learning online courses. 1. Machine Learning (Stanford University) Prof. Andrew Ng, instructor of the course. My first pick for best machine learning online course is the aptly named Machine Learning, offered by Stanford University on Coursera.If you’re itching to learn quilting, it helps to know the specialty supplies and tools that make the craft easier. One major tool, a quilting machine, is a helpful investment if yo... Machine learning is much broader than this one approach. The crucial distinguishing feature of ML from data science is that machine learning's focus is on methods of learning from data. Unlike data models where the relationships of elements is pre-defined by programmers or architects, machine learning algorithms discover the patterns in the ... You have to learn word embeddings, transformers, RNNs, etc. And once you know the basics, you have to learn a new NLP skill. Doing translations is a new skill, making a chatbot is a new skill, word tagging is a new skill etc. NLP SOTA uses deep learning, so if you did DL in CV, you won't have to re-learn the basics of DL. r/MachineLearning. This subreddit is temporarily closed in protest of Reddit killing third party apps, see /r/ModCoord and /r/Save3rdPartyApps for more information. [R] Towards understanding deep learning with the natural clustering prior (PhD thesis) r/math. This subreddit is for discussion of mathematics. 11 votes, 38 comments. true. I use machine learning for my long options portfolio, I use classifiers to establish potential group of candidates then predictors for placing the orders, stop loss is a simple ATR band, wider for calls, narrower for puts, Daily data set with price derivatives and fundamental analysis data to better time entry.Secondly, learning and education is not a baby feeding session nor is it a quick hit with the golden solution. It is the pursuit of finding answers and solutions wherever they may be and using many different sources, however lengthy (e.g. a book) or a 13-minute YouTube clip (which you can scrub through to the end by the way, where the ...Work with language data, transaction data in tables, and even small-sample qualitative surveys. As you progress in your career you'll likely get more specialized but it's important to have a broad base of fundamental skills and analytical insights. - Keep learning. This field constantly changing.Yes, ML is very much possible to be self taught, with the amount of online blogs and free courses on Coursera, it is very much possible. You can check out the popular Andrew NG's Machine Learning course from Coursera and then move on to deep learning.ai course. Another very detailed and in depth ML course will be from NPTEL.We’re trying to set up a Machine Learning lab at our company. It’s been an uphill battle with IT and fluctuating budgets. ... More importantly however, the behavior of reddit leadership in implementing these changes has been reprehensible. This sub will be private for at least a week from June 12th. For more info go to /r/Save3rdPartyApps ...PhDs are indeed quite competitive, as others have described. On the brighter side though, many universities have started to offer masters programs in Data Science & ML (e.g. USF ), which typically have a higher intake (i.e. less competition) compared to PhD programs, and focus on practical application of Data Science & ML, rather than research. 1.569 votes, 81 comments. 387K subscribers in the learnmachinelearning community. A subreddit dedicated to learning machine learningMICCAI and IPMI are A tier conferences in medical image computing (lot of similar themes as AI/ML are applied in these papers) Some applications conferences similar to CVPR or ACL that typically feature ML: FAccT, RecSys, WSDM, TheWebConf, SIGIR, ICDM.MICCAI and IPMI are A tier conferences in medical image computing (lot of similar themes as AI/ML are applied in these papers) Some applications conferences similar to CVPR or ACL that typically feature ML: FAccT, RecSys, WSDM, TheWebConf, SIGIR, ICDM.To become a Machine Learning Engineer, one should follow a structured path that combines education, hands-on experience, and continuous learning. Begin by acquiring a strong foundation in mathematics, statistics, and computer science, as these are fundamental to understanding the underlying principles of machine learning.But though machine learning found the hidden oscillations, “only later did we understand them to be the murmurations.” Editor’s Note: Andrew Sutherland, Kyu-Hwan Lee …Reddit is a popular social media platform that has gained immense popularity over the years. With millions of active users, it is an excellent platform for promoting your website a...The second edition also covers Generative Learning to a deeper extent as well as productionalizing learning algorithms. If you're looking for an RL reference, Sutton and Barto is the gold standard. OpenAI gym/rllib/stablebaselines are …There's really a few different things you could learn with AWS. Machine Learning training using GPU instances. This will likely be the easiest to learn, and it essentially just means allocating a server with a GPU (usually something like a K80 or P100 for $1-3/hr, prorated to the minute), setting it up, and training on it. No. R is maybe a bit better for explorations, but its productization is rly bad. Python has both. It can be used both for explorations and for developing final product. And its getting even better at both those tasks. Programming in Python since ~2003, using R for machine learning since ~2012. In numerical analysis and computer science, a sparse matrix or sparse array is a matrix in which most of the elements are zero. By contrast, if most of the elements are nonzero, then the matrix is considered dense. The number of zero-valued elements divided by the total number of elements (e.g., m × n for an m × n matrix) is called the ...To help you, I've compiled an up-to-date list of 20+ active machine learning and data science communities grouped by platform. 1. Reddit. Reddit is a powerhouse for many active forums dedicated to all areas across AI, machine learning, and data science. Here's a list: r/machinelearning (2M+ members) r/datascience (500K+ members)im currently learning with the kaggle courses and udemy Machine Learning A-Z Any Recommendations on better courses or are these decent Related Topics Machine learning Computer science Information & communications technology Technology comments sorted by ... Reddit . reReddit: Top posts of February 17, 2022.But most of my interest was for the mathematics behind Machine Learning and AI. And most of the ML projects are just programming on keras and stuff. Like there can be maths involved here, just not the heavy kind like we learn in theory, so is there usually much research going on under AI making or refining mathematical algorithms for AI ...Hello guys, I am new to reddit and to machine learning as well. Just yesterday I finished a Hackathon where me and my team made an image recognition AI using MobileNetV2. I don't …A robust machine learning engineering skill set is hard won, just like compilers, operating systems, or distributed systems skillsets. So while you (perhaps thankfully) don’t have to acquire a PHD, getting into ML engineering isn’t a walk in the park. Presented below is an inevitably incomplete, but still fleshed out list of resources for ...The final capstone project in Coursera's Machine Learning and similar specializations is a worthwhile investment, IMHO. So, I probably wouldn't worry much about an individual course certificate, unless you plan to complete a series of courses and do the capstone project. 4. Related Machine learning Computer science Information & communications technology Technology forward back r/learnpython Subreddit for posting questions and asking for general advice about your python code. Hi there, Deep learning is taking over a lot of other machine learning algorithms in industry. I was curious in what applications do other algorithms still outperform deep learning. And what algorithms are they?. I am mostly curious on this over in the industry world. If you could provide in the comments 1. The algorithm 2. The application and 3.Deep learning is a method of machine learning involving at least 1 more "layer" of math between the input and output. An input can be pixels on the screen and the output numbers 0-9 and you want AI that can take an image of a number and determine what number that is.r/MachinesLearn: This is a subreddit for machine learning professionals. We share content on practical artificial intelligence: machine learning…Try to do a couple of machine learning projects. Reason being, for backend development, you may not need a project for internship or even a job, but, for machine learning, it is highly recommended to have some projects in your portfolio which can make you stand out among there, be it an internship or a job or a gig. All the best.I also do a bunch of ML research in Python, as the deep learning stack (particularly for distributed problems) is just not there on the JVM. The Python ecosystem still has better data frames & plotting, as well as the aforementioned distributed deep learning stack, but you can do many things in scikit-learn just as well in Java.569 votes, 81 comments. 387K subscribers in the learnmachinelearning community. A subreddit dedicated to learning machine learningOct 11, 2018 ... ... deep learning. I read Towards Data Science, Machine Learning sub-reddit, WildML and other blogs too. https://www.youtube.com/watch?v ... 1)General Python programming. Usually leetcode type questions about implementing something in Python, or questions about Python's features. Also very helpful to know mundane stuff like pulling data from APIs, formatting strings, and so on. 2)General Machine Learning and statistics questions. These tended to be theoretical. A place for beginners to ask stupid questions and for experts to help them! /r/Machine learning is a great subreddit, but it is for interesting articles and news related to machine learning. Here, … Only deep learning is really better in Python. Advanced statistics and new papers on that realm are much faster integrated to R on the other hand. Deep learning vs adv. Stats For "normal" machine learning use R works as well as Python. R has many packages which might cause confusion compared to Python having pretty much everything in scikit-learn. Without further ado, here are my picks for the best machine learning online courses. 1. Machine Learning (Stanford University) Prof. Andrew Ng, instructor of the course. …r/learnmachinelearning: A subreddit dedicated to learning machine learning.Related Machine learning Computer science Information & communications technology Technology forward back. ... CSCareerQuestions protests in solidarity with the developers who made third party reddit apps. reddit's new API changes kill third party apps that offer accessibility features, mod tools, and other features not found in the first party ... A place for beginners to ask stupid questions and for experts to help them! /r/Machine learning is a great subreddit, but it is for interesting articles and news related to machine learning. Here, you can feel free to ask any question regarding machine learning. Here is the list of books that I gathered to add: The Elements of Statistical Learning. Second Edition. Trevor Hastie, Robert Tibshirani, and Jerome Friedman. Reinforcement learning, An Introduction. Second Edition. Richard S. Sutton and Andrew G. …It will just create an arbitrage and every finance guy would want to exploit it thus killing the option in the long run. I'm not saying that there is no model for trading, but none that can predict the price of a product in the future, especially in forex or oil and that "stood the test of the time". Forex price or oil price are basically some ...Yes, ML is very much possible to be self taught, with the amount of online blogs and free courses on Coursera, it is very much possible. You can check out the popular Andrew NG's Machine Learning course from Coursera and then move on to deep learning.ai course. Another very detailed and in depth ML course will be from NPTEL.Here are our top picks of Reddit’s machine learning datasets. Best Reddit Datasets for Machine Learning. Cryptocurrency Reddit Comments Dataset: Containing … There are many good courses on machine learning available online. Some of the most popular ones include: Skillpro's Machine Learning course by by Juan Galvan: skillpro.io. Coursera's Machine Learning course by Andrew Ng: coursera.org. Fast.ai's Practical Deep Learning for Coders course: course.fast.ai. Specialization - 3 course series. The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This …Related Machine learning Computer science Information & communications technology Applied science Formal science Technology Science forward back. r/buildapc. ... The official Python community for Reddit! Stay up to date with the latest news, packages, and meta information relating to the Python programming language. --- If you have questions or ... coursera – machine learning (first three weeks) 100 page ML book. From now on, three areas of focus will be given for each level: Mathematics, Concrete ML knowledge, and Programming. Level 2 – Competent Developer. Have basic intuition about the math relevant for ML. It's a rendering technique that uses differentiable equations. Of course this is used in machine learning, but the DR itself doesn't have any predictions or "intelligence". Neural rendering is rendering using deep learning. So, of course it should need to use some form of differentiable rendering, but it goes a bit farther. Build a TensorFlow Image Classifier in 5 Min video. Deep Learning cheat-sheets covering Stanford's CS 230 Class cheat-sheet. cheat-sheets for AI, Neural Nets, ML, Deep Learning & Data Science cheat-sheet. Tensorflow-Cookbook cheat-sheet. Deep Learning Papers Reading Roadmap list ★. Papers with Code list ★.
569 votes, 81 comments. 387K subscribers in the learnmachinelearning community. A subreddit dedicated to learning machine learning. Frozen breakfast sandwiches
Mathematics for Machine Learning by Deisenroth. Hands-on ML with scikit learn, keras and TF, 2nd edition (it is substantially better than the previous edition) by Géron. The hundred page ML Book by Burkov. Introduction to ML 4th edition by Alpaydin.Reddit announced Thursday that it would buy Spell, a platform for running machine learning experiments, for an undisclosed amount.. Spell was founded by former … Hands-on ML with scikit learn, keras and TF, 2nd edition (it is substantially better than the previous edition) by Géron. The hundred page ML Book by Burkov. Introduction to ML 4th edition by Alpaydin. These for me are the best books to start with, then you move to more complex and funny books like Murphy or Bishop. Know how ML‘s potential can be utilized to serve themselves (or their teams) resources: coursera – ai for everyone andrew ng – machine learning yearning coursera – machine learning (first … Related Machine learning Computer science Information & communications technology Technology forward back r/OMSA The Subreddit for the Georgia Tech Online Master's in Analytics (OMSA) program caters for aspiring applicants and those taking the edX MicroMasters programme. It depends on whether (advanced) cognition can be designed in different ways. If there is only one simple way to lead to cognition, then it is very insightful to use that knowledge for machine learning approaches. The null hypothesis is probably that this is true since many features of biological organisms are a result of convergent evolution.569 votes, 81 comments. 387K subscribers in the learnmachinelearning community. A subreddit dedicated to learning machine learning A place for beginners to ask stupid questions and for experts to help them! /r/Machine learning is a great subreddit, but it is for interesting articles and news related to machine learning. Here, you can feel free to ask any question regarding machine learning. Hello. I am very interested in learning ML and AI. I did take a basics course still in the beginning of university, and I would like to deepen my knowledge on this topic, which I find deeply …Related Machine learning Computer science Information & communications technology Applied science Formal science Technology Science forward back r/ITCareerQuestions This subreddit is designed to help anyone in or interested in the IT field to …Referenced Symbols. +0.35%. The Federal Trade Commission has launched an inquiry into Reddit’s licensing of user data to artificial-intelligence companies — just days …350K subscribers in the learnmachinelearning community. A subreddit dedicated to learning machine learning. Premium Explore Gaming. Valheim ... View community ranking In the Top 1% of largest communities on Reddit. 7 Best Free Machine Learning Courses Online …Machine learning algorithms are at the heart of many data-driven solutions. They enable computers to learn from data and make predictions or decisions without being explicitly prog... Specialization - 3 course series. The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications. I am not sure which degree is best for getting into machine learning the obvious choice seems to be computer science but I have seen people say that maths, statistics or data science can be ….