striker_axel

So, recently i started giving out interviews. I have 7+ years of experience so one or two design rounds are expected. Keeping that in mind i revised my concepts on distributed system and read few famous papers on distributed system. it was fun visiting those concepts again. Also, as advised i watched few scaling videos on youtube (i.e Design Uber etc.)

I have experience building system from scratch and depending upon the requirement i have scaled few services in my organization.

So, my expectations from the design round was to have open-ended discussion with interviewer on certain component and discussing drill-down component architecture, scaling issues, drawbacks etc.

But For me at least, reality is quite different. I was asked to design BookMyShow ( Movie booking system ) in full. I mean the interviewers expectation was to just draw the components, write the api and design schema. He will understand my work by looking into it.

I have given 5+ interviews as of now ( got offer from some of them). But i feel like design round wasn't justified.

Hi Everyone, I have just recently joined a healthcare company and there are a lot of new terminologies that I don't understand ( coming from an e-commerce background). I joined this company because I want to build my career in healthcare or even start a startup after some time. I think healthcare with AI will be the future. Following this vision, I want to learn about the industry from the inside. But there is a lot to learn. Any ideas on how should with the foundation then move to more complex terminologies in the healthcare industry.

Media is saying the capitol siege was conspired on parler. Maybe they are right. But is it okay for corporations take step and ban the Parler app ( AWS is planning to terminate their hosting)? I mean such as decision should be taken by Court not corporates (like google, facebook and twitter ).

Hi HN, I have started my study on DeepLearning from March. Initially, I went with no Math courses like fast.ai and Started working on code. But to implement something new I needed a Deeper Knowledge on Research papers so I have completed the following courses.

1. Andrew Ng's DeepLearning Specialization

2. NLP from Stanford.

then I went to https://www.deeplearningbook.org book by Ian Goodfellow. But the unsupervised learning part too abstract. that I feel like I am still missing the foundation for understanding deeplearnning.

Any recommendation?

Recently, I started studying Machine Learning being from a programming background I choose fast.ai to be my headstart but after watching few videos i find fast.ai to be more of a tooling (high-level api ) knowledge. Being not able to visualize why CNN, RNN, Batch Normalization, etc. are created. I just go by the blind approach of applying CNN to image problems and RRN to every sequential problems but i had found that for some case we can use RNN in images ( only relating image captioning ) and CNN for NLP.

To make my knowledge more concrete i started reading deeplearningbook ( by Ian Goodfellow ) and it is a great book for getting in-depth understanding but this book is an only theory (no practical code) and i seem to forget the concepts after a week or so.

So my question is how do you retain the concepts or tricks ( like initializing hyperparameter based on activation function used, etc. ) for practical projects? Or what your approach to learning this overwhelming technology?