Machine learning reddit.

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.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 ...The better you are at math, the more intuitive you will find working with machine learning models. If you suck at math, you can still use models and functions that other people have built, but will struggle to build and maintain your own. To be competitive in the job market, you need to be really quite good at math.There’s more to life than what meets the eye. Nobody knows exactly what happens after you die, but there are a lot of theories. On Reddit, people shared supposed past-life memories...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.

If you only plan on using other people's fully developed code, you probably don't need to learn the math. But then you really don't know machine learning then, you just understand how to use software libraries and abstractions on top of machine learning algorithms. Although I personally enjoy learning to understand the mathematics behind ML, I ... Check out Ace the Data Science Interview — it covers statistics, machine learning, and open-ended ML case study interview questions. The book focuses more on the foundations of the field + interview questions related to classical ML techniques, rather than something like reinforcement learning, because honestly, that's what 90% of Data Science & ML …

Let’s take a walk through the history of machine learning at Reddit from its original days in 2006 to where we are today, including the pitfalls and mistakes made as well as their …

Reddit disclosed the Federal Trade Commission is looking into its sale, licensing or sharing of user-generated content with third parties to train artificial intelligence models. The … 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. Generally for R/Python vs Java: R and Python are much easier to play around with, try out ideas, etc. Java is a very verbose language. It might be more robust and since it's compiled it is decently fast, but it's NOT a language to easily try stuff out. It's an enterprise-y language, which can be sort of a cludge if you want to write some quick ...Using Machine Learning to Solve Reddit’s “Rating-less ” Problem. Looking at the way in which Reddit’s marketplaces work led me to construct an algorithm to help solve the …

Hey Reddit, I am sharing a curriculum I created and followed that has helped me transition from a non technical job (marketing) to a career where I am now building deep learning training pipelines, prototyping apps and deploying them online. ... Start by learning how to code, then take Andrew Ng's machine learning course. That's a great start.

If you work with metal or wood, chances are you have a use for a milling machine. These mechanical tools are used in metal-working and woodworking, and some machines can be quite h...

Michaels is an art and crafts shop with a presence in North America. The company has been incredibly successful and its brand has gained recognition as a leader in the space. Micha...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 … 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. The certification especially a paid one helps u stand out against the thousands of people who don't have one. It shows interest basically, however it's not a game changer, more of a profile booster. More importantly tho it's the knowledge u gain. You can try deeplearning.ai although you would probably have heard about them already. Recommendations for learning mathematics for machine learning. I'm having a bit of a hard time keeping up with the Mathematics for Machine Learning Course by Andrew Ng. I was …

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 ... The common saying is "working with AI means spending 80% of your time working with data." Currently, working with AI means two things: either you do research (and you have to be somewhat exceptional for that), or you work in the "real world", which means you spend most of your time working with data. This is the impression I have gotten, and I ... 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, …A compound machine is a machine composed of two or more simple machines. Common examples are bicycles, can openers and wheelbarrows. Simple machines change the magnitude or directi...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 ...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 to make this information …

Michaels is an art and crafts shop with a presence in North America. The company has been incredibly successful and its brand has gained recognition as a leader in the space. Micha...

The certification especially a paid one helps u stand out against the thousands of people who don't have one. It shows interest basically, however it's not a game changer, more of a profile booster. More importantly tho it's the knowledge u gain. You can try deeplearning.ai although you would probably have heard about them already. 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.A milling machine is an essential tool in woodworking and metalworking shops. Here are the best milling machine options for 2023. If you buy something through our links, we may ear...May 30, 2023 ... You can learn machine learning without being strong in math by focusing on practical implementations, utilizing high-level libraries, ...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...Data mining: A human looking for something in a large dataset. Machine learning: Computer programs (AIs) that learn from a large dataset to produce similar, original results. EgNotaEkkiReddit. • 3 yr. ago. They are related, but not all data mining is ML and not all ML is data mining. Data Mining is a wide field that involves finding ...Machine Learning is not to be taken lightly and its not simply something you can learn by asking a few questions on reddit. It might take you 2 years to understand everything starting from …

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 …

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.

C++ is used in the development of frameworks and libraries such as Tensorflow but as a user you don't need to know any C++. Yeah, this seems to be true of many high power computing applications. The building blocks of things like simulations, machine learning, encryption breaking, and genetic algorithms don't change that much. r/machinelearningmemes. End-to-End MLOps platforms such as Kubeflow, MLflow, and SageMaker streamline machine learning workflows, from data preparation to model deployment. These platforms include components such as source control, test and build services, deployment services, model registry, feature store, ML metadata store, and ML pipeline ... 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. 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. A milling machine is an essential tool in woodworking and metalworking shops. Here are the best milling machine options for 2023. If you buy something through our links, we may ear...Machine Learning is mathematics first, and programming second. Machine Learning research is currently (and likely in future) dominated by Ph.D. graduates in Physics, Mathematics, Statistics, and Computer Science. Undergraduate studies in a quantitative discipline like mathematics, statistics, or physics will probably be the best place for you ...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 ...After some digging, I narrowed it down to these two candidates: Linear Algebra and Optimization for Machine Learning: A Textbook by Charu C. Aggarwal. Introduction to Linear Algebra by Gilbert Strang. Would very much appreciate to hear your experience with either of them! EDIT: Wow, thank you guys! 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. 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. 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.

Mar 2, 2022 ... ... reddit.com/r/MachineLearning/comments/t55lbw/d_whats_your_favorite_unpopularforgotten_machine/hz3hd4h/. You can think of clustering as a kind ...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 …Here are the math classes i would take in the CS-program: - Discrete Maths. - Calculus for CS-students (less proof-heavy) - Linear Algebra (again less proof-heavy) - Discrete probability theory. - Nonlinear optimization. - Numerical programming. - Modelling and simulation. Do you think this will me prepare for ML-Research, especially, if i want ... I’ve read a lot of posts asking for recommendations for textbooks to learn the math behind machine learning so I figured I’d make a self-study guide that walks you through it all including the recommended subjects and corresponding textbooks. You should have more than enough mathematical maturity to work through ESL and the Deep Learning ... Instagram:https://instagram. puppy versus kittengilded age tv showhair products for wavy hairbest italian north end Basically, if you are implementing and training from scratch, focus on something you can train with a smallish dataset in a reasonable period of time. I would generally steer away from LLMs and object detection / segmentation models as they require more resources to train that are commonly available! 22. TheInfelicitousDandy.The performance of machine learning models heavily depends on the quality of input data, yet real-world applications often encounter various data-related challenges. ... Link posts must include context (ie: a comment in the reddit … 2023 camry xse v6shave pubic hair Buying a used sewing machine can be a money-saver compared to buying a new one, but consider making sure it doesn’t need a lot of repair work before you buy. Repair costs can eat u... how to repair foundation cracks This subreddit is temporarily closed in protest of Reddit killing third party apps, see /r/ModCoord and /r/Save3rdPartyApps for more information. ... The dataset also has the projects tag so you can search for machine learning/deep learning/etc. The project has no forks, redundant file and were checked to be software projects ...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.r/learnmachinelearning: A subreddit dedicated to learning machine learning.