I think I am able to develop end-to-end ML projects. However, my question was about building a career in this space, how to move from junior to senior, from senior to being an expert in the field.
Good paper, I was wondering what is the state-of-art of using Neural Networks for Text Segmentation, Text Lemmatisation, Part-of-speech Tagging. Morphological approaches is dominant in this space.
I found RSS feeds to be better alternative to read the news beyond the filtering bubble that our social media platforms create.
There was an interesting tool to monitor RSS list of newspapers[1] on HN sometime ago. I wish that this tool [2] is hosted somewhere to easily get notification on my slack without setting it up or managing it. With load of information we face everyday, the idea of monitoring RSS feeds through Slack interface is very interesting.
How about SageMaker, Can we include it in this list. I played with SageMaker sometime ago and it helps you build a whole pipeline to host your models, in addition to host your notebook and bridge the gap between data scientists and data engineers.
You don't need all of this. All what you need is to request your data from twitter (Your Tweet archive
> https://twitter.com/settings/account). Iterate through the csv file and use tweet_id to unlike, remove or do what you want through their Twitter API.
Source: I have done it before, and it took less time/work than what you have stated.