Reddit machine learning

It'll set you back a lot of money, but it's an investment in time and money, and in theory should return ten times as much. #39 in Best of Coursera: Reddsera has aggregated all Reddit submissions and comments that mention Coursera's "Machine Learning" specialization from University of Washington.

The machine learning model will score each comment as being a normal user, a bot, or a troll. Try it out for yourself at reddit-dashboard.herokuapp.com.schwah • 2 yr. ago. Step 1: Use Python. All of the best ML libraries are Python. Prety much all of the compute heavy stuff you'd want to do should be through library implementations (which are written in highly optimized C++/CUDA) so you aren't going to see any performance benefit in writing in C++ vs Python.It’s a machine learning approach that is somewhat related to metalabelling. In the formal approach there’s a defined state, action, and reward. ... Additionally, consider incorporating data from social media platforms like Twitter and Reddit, where investors and traders often discuss market sentiment and individual stocks. By tapping into ...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.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 know the trivial stuff of mlops life cycle and tools, but I'm still not really good in software engineering practices and the "engineering" part of machine learning. The thing is, I think that mlops, deep learning and GenAI evolves really fast, and most tools become deprecated quickly (at least I feel it)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 ★.Talking to a friend that’s struggling with their mental health is tricky. You might be concerned about saying the wrong thing or pestering them with too many phone calls and texts.... What should I do. Where should I start. I know a good amount of python and js. Currently in 189, and I agree. It's a good baseline for if you're entirely lost and need some reinforcement/starter of where to develop strong ML skills, but as for learning the actual skills lmao good luck learning all that on your own. Referenced Symbols. +0.35%. The Federal Trade Commission has launched an inquiry into Reddit’s licensing of user data to artificial-intelligence companies — just …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...

This subreddit is for all those interested in working for the United States federal government. Since the application process itself is often nothing short of herculean and time-consuming to boot, this place is meant to serve as a talking ground to answer questions, better improve applications, and increase one's chance of being 'Referred'. With enough data, matrix multiplications, linear layers, and layer normalization we can perform state-of-the-art-machine-translation. Nonetheless, 2020 is definitely the year of transformers! From natural language now they are into computer vision tasks. Honestly, I had a hard time understanding its concepts. This post explains the transformer ... 87 votes, 10 comments. 387K subscribers in the learnmachinelearning community. A subreddit dedicated to learning machine learningGetting started in machine learning can be a daunting task, but there are many resources available to help you learn the fundamentals and start building your own projects. ... You can find communities on social media platforms like Twitter and Reddit, as well as on forums like GitHub and Kaggle. Some great communities to check out include: r ...A laptop is perfectly capable of most non-deep learning data science tasks. For deep learning, you can still build the model and run through a few epochs to see if the losses are decreasing. At that point you could put the model on the cloud. In …

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Anything to do with machine learning (especially deep learning) and Keras/TensorFlow. Users share projects, suggestions, tutorials, and other insights. Also, users ask and …It’s a machine learning approach that is somewhat related to metalabelling. In the formal approach there’s a defined state, action, and reward. ... Additionally, consider incorporating data from social media platforms like Twitter and Reddit, where investors and traders often discuss market sentiment and individual stocks. By tapping into ...Jun 16, 2022 · Reddit announced Thursday that it would buy Spell, a platform for running machine learning experiments, for an undisclosed amount.. Spell was founded by former Facebook engineer Serkan Piantino in ... 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 … 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. Although machine learning might not sound too complex, there is a shitton of theory behind it. Just keep yourself busy with learning something new every day or two and you should be golden. Reply reply

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... ML in Windows, Bing, Visual Studio etc are made with ML.NET. Reply reply. PrototypeV5. •. Note: Not having all the libraries in C# is an opportunity to create them (which allows you a hands-on opportunity to understand the algorithms). Reply reply. Individual-Trip-1447. •. Yes, C# is suitable for AI (Artificial Intelligence). Referenced Symbols. +0.35%. The Federal Trade Commission has launched an inquiry into Reddit’s licensing of user data to artificial-intelligence companies — just … ADMIN MOD. [D] ICLR 2024 decisions are coming out today. Discussion. We will know the results very soon in upcoming hours. Feel free to advertise your accepted and rant about your rejected ones. Edit 2: AM in Europe right now and still no news. Technically the AOE timezone is not crossing Jan 16th yet so in PCs we trust guys (although I ... Calculus 2 is therefore much narrower in its scope than Calculus 1. Finding antiderivatives isn't terribly important in applications because one usually has a computer numerically integrate anyway. Studying sequences does have practical applications, but I'm not sure if it pertains to machine learning. As for difficulty, you obviously want to ... 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 ★. I would argue that learning machine learning with ONLY python is kind of useless for practical senses like getting a job or making useful projects. Even if you could've done it somehow you really wouldn't know how it works and how to make further progress. ... Dude this sub Reddit is about learning not discuss politics Reply reply More replies.This is thousands of pages. Algebra, Topology, Differential Calculus, and Optimization Theory. For Computer Science and Machine Learning. Jean Gallier and Jocelyn Quaintance Department of Computer and Information Science University of Pennsylvania Philadelphia, PA 19104, USA. e-mail: [email protected].

Define the Problem. As you may have guessed I was tasked with using machine learning to do what you just tried to do above! In other words, creating a classification model that can distinguish which of two subreddits a post belongs to. The assumption for this problem is that a disgruntled, Reddit back-end developer went into …

/r/MachineLearning: Research, News, Discussions, Software @ Machine Learning, Data Mining, Text Processing, Information Retrieval, Search Computing and alikefifthsquad. For begginers: •Hands-On Machine Learning with Scikit Learn, Keras and Tensorflow (3rd Ed.) - (This was actually my favourite one, as it covers a lot of topics) •And Introduction to Statistical Learning with Applications in R (2nd Ed.) - (If you like R) •Deep Learning with Python (2nd Ed.) •Deep Learning - (A classic from ...Related Machine learning Computer science Information & communications technology Applied science Formal science Technology Science forward back r/gamedev The subreddit covers various game development aspects, including programming, design, writing, art, game jams, postmortems, and marketing.Learn how to use Reddit's machine learning datasets for content moderation, sentiment classification, and more. Find out the best Reddit datasets for … Machine Learning Hard Voting and Soft Voting. Ensemble Learning in the field of Machine Learning is using multiple Machine Learning models. and aggregating the predictions of each model to make the final prediction. Aggregating basically. means combining the predictions in some way to form the final prediction. Are you looking for an effective way to boost traffic to your website? Look no further than Reddit.com. With millions of active users and countless communities, Reddit offers a uni...I want to learn machine learning just to make some AIs to play video games for me, improve macros, or just use it to mess around and make hobby projects like programs that search the web for me. I just finished learning multivariable calculus and portions of linear algebra and probability theory, but I do not enjoy the math so much. Cohere's intelligent prior authorization solutions reduce administrative expenses while improving patient outcomes. The company is a winner of the TripleTree iAward and has been named to both Fierce Healthcare's Fierce 15 and CB Insights' Digital Health 150 lists. 🌎 Location: United States. 💵 Salary: USD 130k-160k. Some of the benefits to science are that it allows researchers to learn new ideas that have practical applications; benefits of technology include the ability to create new machine...

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Both levels of the nested cross-validation used class-stratified random splits. So the splits were IID: independent and identically distributed. The test data looked like the validation data which looked like the training data. This is both unrealistic and precisely how most peer-reviewed publications evaluate when they try out machine learning.17-Nov-2020 ... The Machine Learning algorithms that you use tend to be simplistic and limited to what your senior engineer understands well. You don't get as ...Having recently worked with a machine learning consultancy in Melbourne I found there were two roles data scientists : people with a statistical and mathematical background who could also code, they worked on keeping up to date with research, defining the problem to be solved, exploratory data analysis, model selection and training, proof of concept demo 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 app. Redirecting to /r/MachineLearning/new/. 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. As a part of the Reddit Machine Learning Engineer interview, you will need to go through multiple interview rounds: 1. Phone screening - The phone screening is a quick call to discuss your background and ML experience.. 2. Technical Round- You will be asked to build a machine learning model based on data provided by the interviewer.This round is … 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 ... I want to learn machine learning just to make some AIs to play video games for me, improve macros, or just use it to mess around and make hobby projects like programs that search the web for me. I just finished learning multivariable calculus and portions of linear algebra and probability theory, but I do not enjoy the math so much. ….

Instead, you combine best practices to create an algorithm effectively. Then you create a production ready solution (as a micro-service or on device) and make sure that it's performing as expected. Including monitoring, retraining, and other types of maintenance. 6.04-Mar-2023 ... There is a stupid amount you have to know, in addition to needing good communication and soft skills. You probably would take a pay cut. Doesn't ...The real learning starts when you begin to absorb someone else's concept then turn it into your own so you can work on your own projects. 4.5) [Optional] There are tons of specialized fields in ML, you should have enough foundations and intuitions to go in more specialized fields. eg computer vision, robotics etc. Machine Learning Hard Voting and Soft Voting. Ensemble Learning in the field of Machine Learning is using multiple Machine Learning models. and aggregating the predictions of each model to make the final prediction. Aggregating basically. means combining the predictions in some way to form the final prediction. 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./r/MachineLearning: Research, News, Discussions, Software @ Machine Learning, Data Mining, Text Processing, Information Retrieval, Search Computing and alike30-May-2023 ... Work is quite demanding so whatever time I get, I try to search for new stuff happening in Computer Vision/Deep Learning space. I usually rely ...Machine learning has become a hot topic in the world of technology, and for good reason. With its ability to analyze massive amounts of data and make predictions or decisions based... Reddit machine learning, [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1], [text-1-1]