For anyone starting on a serverless journey, AWS lambda is just amazing. You write the code, invoke the function and it does the job for you. Hold on, is it really doing as expected? I mean what about the execution time? How do I ensure that my lambda function is performing optimally with minimum costs? This is the question that ponders everyone when they start to productionize lambda functions. Believe me, the kind of questions I get around lambda functions is just crazy:
A practical implementation of time series analysis using facebook’s opensource library fbprophet
This article is a follow-up of one of my earlier article Time Series Analysis — A Beginners Guide. If you are new to time series, I strongly recommend you to read through that article before this implementation example.
I always like to have a different environment setup for each suite of projects. So go ahead and use the below commands to setup a new environment and install software's via anaconda prompt. Once the software’s are installed, open up the jupyter notebook and we are ready to go.
A brief overview of the different aspects to look for when doing time series analysis.
Time series is statistical data that is arranged and presented in chronological order. Time Series Analysis is predicting the data for the future based on the past data in the time series. For e.g. If we know the sales of an organization from 2015 to 2020, we can use this data to predict the sales for 2021 and beyond. But bear in mind that this is only the prediction and not exact number. Its a prediction stating that sales will be somewhere near to this…
API gateway is great when it comes to exposing your APIs publicly and you will find a lot of blogs and videos around it. However, most organizations want to define private APIs for consumption by other sub-systems within the organization. I had a lot of struggle learning how to define private APIs with custom DNS. This article gives a step-by-step guide on how to achieve this. Below is the depiction of what we are going to achieve at the end of this article.
Step 1: Create an interface VPC endpoint
Login to your AWS console and select the VPC service…
Different Approaches to Name Matching
This is one of the most commonly used approach. The basic idea behind fuzzy match is to measure the edit distance between 2 strings. What does it take to convert from Source String A to Destination String B?
There are many approaches to fuzzy match. But the 2 most common ones are Jaro-Winkler distance and Levenshtein distance. Let us understand how each one of them work.
Here is the more formal definition of this algorithm from Wikipedia
The Jaro–Winkler distance is a string metric measuring an edit distance between two sequences.
The lower the Jaro–Winkler…
This is a continuation from my previous article. If you haven’t read that, I strongly suggest you to read that first to get a high level overview of Deep Learning concepts. Here is the link to Part 1 (Deep Learning — Beginners Guide)
I could have dived deep into more theory and math part of activation functions, loss functions, optimizers etc. But I thought, Its a good idea to get our hands dirty and implement the first Artificial Neural Network (ANN) to get an understanding of the tool set. So let get started.
Ever wondered what is deep learning and how its changing the way we do things. In this series of tutorials, I will dig into the terminology used in the space of deep learning. A complete look at the mathematics behind activation functions, loss, functions, optimizers and much more. Along the way, I will also share links which I felt are useful rather than mentioning it to the end of the article.
Deep Learning: To put this in simple words, “Deep learning is all about making the machine to think and learn like human brains do”. In order to do this…
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