FanduTech – Data Science Product Development and Consulting:

Blogs

1. How to leverage Data Science in Retail Industry (Sept. 2, 2020)

   This blog details out how data pipeline can be leveraged to ingest data and do analytics using AWS analytics stack in retail industry, particularly consumers domain. It also describes how various analytics report, a.k.a. "vanity metrics" reports, and ML can be harnessed to prop up growth.

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2. Building AWS Data Pipeline for cross-account resources (Sept. 1, 2018)

   How you can easily build an automated cross-region/cross-account data pipeline using AWS Data Pipeline and AWS lambda.

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3. Text Classification with Deep Learning in Keras (March 30, 2017)

   This blog post explains how Keras library is used to classify email texts as spam or ham.

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4. Unpickling issue in multi-module Python project (Jan. 18, 2017)

   This post mentions the issue with unpickling in case of multi-module python project set up, and the way to resolve it.

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5. Is Big Data Just a Fad? (Aug. 13, 2015)

   Is big data just a fad? Considering all of its use cases and its integration into IoT, science and machine learning, it might be more than just a buzzword.

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6. Prop Up Development and Testing with DynamoDB Local in Java (Sept. 28, 2013)

   How AWS DynamoDB NoSQL database can be set up locally in development environment and how it can prop up and expedite development process.

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7. Taming the Performance Beast – a Practitioner’s Way (Part 1) (Jan. 4, 2013)

   Performance tuning can be a complex and time consuming process with good chance of you getting frustrated if you do not have abundant patience, especially for products/applications that have high demand on performance but have poor foundation with respect to it. It is an ongoing process – often long and frustrating, that works in an iterative mode and needs to be treated and managed differently from normal development process. One should take a note that this is not about a silver bullet but concerted, honest and persevered effort. If something does not go well, it can be horribly wrong with the potential of rendering the application worse performing than it was initially. This article tells about first-hand real-time experience with tuning including suggestions and guidelines on how one should approach it in order to successfully achieve it.

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