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Since the beginning of the last month, I have started to produce video content about LangChain. Video content is easier to engage with on a complex topic like ML. Also, because I consider the AiEdge Newsletter an educative platform for Machine Learning, I think it is better to learn if the content builds from the one of the past week to have more continuity in the learning experience.
I have been enjoying creating those videos, and I would like to make more of them! But before doing so, I wanted to get your input on the next subject I should focus on:
The subjects in this poll are the ones I feel comfortable educating people about, but please don’t hesitate to suggest others in the comments. Here is my reasoning about those subjects:
Introduction to Data Science - Machine Learning: the videos would be spread across three subjects: data wrangling with Pandas, Statistical data analysis, and Machine Learning. I have taught this course at the university, and it was an excellent way for students to get the students ready to become Data Scientists.
Introduction to Machine Learning System Design: to me, that is the most essential skill if you want to become a senior engineer. The ability to design ML solutions end-to-end while communicating with different teams and people with different skill sets is fundamental to building successful products.
Introduction to Recommender Systems: Recommender systems are everywhere and are the ML applications generating the most revenue across industries. I want to provide material for people to understand how the latest rec systems are designed.
How to train and fine-tune LLMs: this type of learning material can be hard to find these days, but there is a gold rush in hiring people with this type of skill. I want to focus on how to build those in practice.
Let me know about your thoughts on the subjects. Thank you for subscribing!
What Video Content Would You Like to See?
Second.
Being new to AL/ML, the first thing I have noticed is there is little focus on working with data, but when I talk to seasoned data scientist its where they spend the bulk of their time.
All the training I have seen and worked through has always used pre-formated datasets, so of course, when I started my first real-world project and had to work with raw data I was struggling to get it formatted correctly and optimally.
Most software engineers I show these datasets to are completely unfamiliar with their structure and how to use them.