Why you should read this guide to Personal Finance? — Part II — InvestmentsPART I — https://medium.com/@nehajirafe/why-every-indian-taxpayer-should-read-this-guide-to-personal-finance-part-i-cashflows-36e3afe960fbDec 13, 2022Dec 13, 2022
Why every Indian taxpayer should read this guide to Personal Finance? — Part I — Cashflows“Oh, My husband manages all the finances; I need not worry.”Dec 13, 2022Dec 13, 2022
5 Lessons from the Psychology of MoneyTop 5 Lessons from The Psychology of Money” by Morgan House!Nov 28, 2022Nov 28, 2022
7 ways you can make your resume stand out1. Use ATS Compliant template: ATS stands for application tracking system. Most people don’t think about it, but where does your resume go…Nov 15, 2022Nov 15, 2022
Hinge Loss : [Machine Learning Bite Size Series]The Machine Learning Bite Size Series is aimed at explaining the terms in a simple 1 minute read for a quick reference.Feb 16, 2021Feb 16, 2021
What the Foo-Bar (google) ?Here I am sharing my experience with the famous google foo bar challenge which I have attempted multiple times (directly and indirectly)Dec 26, 2020Dec 26, 2020
How to make Jupyter Notebooks Extensible and ReusableAll those who use Jupyter notebooks for data analysis or machine learning workloads , know the pain of the “copy — paste” cycle for…Jul 10, 2020Jul 10, 2020
Data Modeling — Designing Facebook style “comments” with SQLLet’s agree , we all have used the “comments” section of some or the other social networking site.Jul 9, 20208Jul 9, 20208
Using FFT to analyse and cleanse time series dataOften when dealing with IOT data , the biggest challenge is encountering unexpected noise, this noise can be very annoying when you want…Apr 15, 2020Apr 15, 2020
Published inAnalytics VidhyaHow to filter noise with a low pass filter — PythonRecently while I was working on processing a very high frequency signal of 12.5 Khz , i.e. 12500 samples per second or a sample every 80…Dec 27, 20199Dec 27, 20199
![Hinge Loss : [Machine Learning Bite Size Series]](https://miro.medium.com/v2/resize:fill:160:106/0*YKKIecAETOho-U3S.png)
![Hinge Loss : [Machine Learning Bite Size Series]](https://miro.medium.com/v2/resize:fill:320:214/0*YKKIecAETOho-U3S.png)
