How to actually learn AI/ML: Reading Research Papers
ฝัง
- เผยแพร่เมื่อ 17 มิ.ย. 2024
- Ready to master AI/ML and boost your career? I'll walk you through the essential steps and strategies to effectively navigate Artificial intelligence or machine learning-related research papers in the ever-evolving tech field.
We'll break down the process of reading research papers, understanding complex concepts, and building a solid foundation for a successful AI and machine learning engineering career. Whether you're a software engineer looking to upskill or an aspiring ML or AI engineer, this guide is tailored for you.
I’ll also share where exactly to find the AI papers based on your goals and explain the resources listed on our website:
✅ AI research papers
www.exaltitude.io/job-seekers...
📎 Other Resources:
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✅ FREE Study Plan to Learn AI/ML Engineering FAST with ChatGPT
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Hi, I'm Jean, Founder of Exaltitude. I've been working in tech for the past 15 years as an engineer, an engineering manager, and a team builder. I was the 19th engineer at WhatsApp and worked with Facebook as an Engineering Manager for six years after the $19B acquisition. I'm excited to share the ins and outs of a Software Engineering career based on my experience as a hiring manager for top tech companies.
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✅Get FREE resources on latest AI research papers
www.exaltitude.io/job-seekers?
I'd like to see more discussions of "fake learning" vs "real learning" in AI/ML fields.☺
Thanks for teaching us. These type of content is really rare in on YT.
Thank you for educating and inspiring us 🎉❤
🎯 Key Takeaways for quick navigation:
00:13 To *master AI/ML, reading research papers is crucial. Navigating these papers is a skill to stay ahead in the field.*
01:38 Compile *a list of 5-10 papers on a specific topic. Reading them linearly isn't efficient; scanning and setting realistic goals matter.*
02:04 Set *realistic goals based on your level: 15-20 papers for foundational grasp, 50-100 for deep understanding. Start with 5-10 if exploring.*
03:15 Efficiently *scan titles, abstracts, and figures first. Sample about 10% of each paper to decide if it's worth diving into.*
04:35 Skip *sections liberally, focusing on abstracts, intros, and conclusions. Don't get discouraged if some parts are challenging; practice improves understanding.*
05:28 Regularly *reading papers builds a strong knowledge base, making you stand out in the long term. Consider it an investment in your career growth.*
06:21 Recommended *sources for finding research papers: Papers with Code, Distilled AI, Deep Learning Monitor, and Archive Sanity. Each has its pros and cons.*
Made with HARPA AI
Very helpful video ❤
Couldn't help but subscribe to your channel, hoping to learn a lot
Thanks for subscribing! Let me know if you have any questions or suggestions for future content
Thank you so much for sharing these nifty tips!
You are so welcome!
Do you think one should get completely comfortable with all the prerequisites of a method discussed in the paper? Sometimes there is too much of that (for a not-so-experienced reader)? What kind of code implementation details should you care about, if any, aside from reading the paper?
Sure thing! It's good to understand the basics of a method from a research paper, but you don't have to stress about every little detail, especially if you're not super experienced. Just focus on the main ideas first.
When it comes to the code part, try to get the overall picture rather than getting stuck in all the tiny code details. Later on, if you want to, you can dig into the code more if needed
I cant find 'distilled AI List of research papers', could anyone provide me link
Links to the sites referenced in the video are on our website www.exaltitude.io/job-seekers? which is also in the video descriptions
How does one build familiarity with all the scary math notation?
Before reading ,i would highly recommend taking a free course on ML mathematics . But if you have an engineering degree you can skip those , its basically the things they taught you in the Uni (calculus 1,2,3 , probability,statistics,queuing theory etc).
Many such notations can be found on wikipedia. Look for "Glossary of mathematical symbols". On that page, you'll also find links to more specific lists of math symbols.
Mam how to do cold calling properly when searching for a job after a big career gap of 5 yrs due to family reasons ? I am an hvac engineer by profession trying to get back into work by looking for different job hunt methods..
This is a great question for our upcoming LinkedIn event. Please ask here and I’ll answer during the q&a Landing Dream Interviews: Mastering LinkedIn for Software Engineers
www.linkedin.com/events/masteringlinkedinforsoftwareeng7138971303499235328/
@@exaltitude Okay ✅
Day 1: of following you
Thanks for following!
Hey i love your videos ❤ but as a subscriber i wanna give you a suggestion your voice is too sharp please edit the audio just the cut off high pitches then it will be soothing while we listen to this as a podcast 😅😅 ,yeah i actually listen to and learn from you guys while coding 😊
Thanks for the suggestion. I do all the editing myself so I’ll keep take it into consideration. Out of curiosity what device are you watching from? I noticed the sound quality is very different on my iPhone vs computer.
@@exaltitudeon my iPhone 🙂
I disagree. I am also listening from iPhone and she sounds normal. It might just be you, individually.
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bro