How do you stay up to date with deep learning research?

How do you stay up to date with deep learning research?

Those are: conferences, Twitter, engineering blogs, newsletters, research papers, and YouTube.

1. CONFERENCE. At the Rework Deep Learning Conference.
2. TWITTER. Example Deep Learning News on Twitter.
3. ENGINEERING BLOGS AND EMAIL NEWSLETTERS.
4. RESEARCH PAPER.
5. YOUTUBE (2019–04–13 Update)

How do data scientists stay up to date?

Social media sites are an easy and quick way to stay up to date on the latest trends, said Silge. Whether it’s new skills, job openings, or best practices, many working professionals share their interests on sites like LinkedIn and Twitter, making those sites a great starting point for staying in the loop.

How do you do a good ML research?

In fact, there are several good ways.

1. Read a lot of papers, and assess them critically.
2. Work in a research group with other people working on similar topics.
3. Seek advice from experienced researchers on what to work on.
4. Spend time reflecting on what research is useful and fruitful.

How do I track and follow the latest ML research?

Create a Twitter account and follow other researchers Most ML researchers that are relevant for my field tweet about their latest research papers. By simply following them and checking my twitter account a couple of times a week, I can keep track of their work.

How do data scientists keep learning?

1. Go to events and join communities.
2. Focus on asking the right question, not how to use the right tool.
3. Participate in Kaggle competitions.
4. Take online courses.
5. Keep reading books, blogs, and articles.
6. Next steps.

How do you stay up to date with papers?

How to keep your head above water

1. Set up citation alerts for your own articles.
2. Set up new article alerts for academics in your field.
3. Set up new article alerts for key topics in your field.
4. Check Google Scholar’s “my updates” once a month.
5. Subscribe to Table of Contents alerts.

How do I become an AI researcher?

Steps to Becoming an AI Engineer

1. Step 1: Obtain a Bachelor’s Degree in Computer Information Science.
2. Step 2: Sharpen Technological Fluency.
3. Step 3: Seek a Position within the AI Field.
4. Step 4: Stay Current on AI Trends.

How do I organize my machine learning project?

Overview

1. Planning and project setup. Define the task and scope out requirements.
2. Data collection and labeling. Define ground truth (create labeling documentation)
3. Model exploration. Establish baselines for model performance.
4. Model refinement.
5. Testing and evaluation.
6. Model deployment.
7. Ongoing model maintenance.