Yohohohohoho (OnePiece reference)!, tech enthusiasts! Welcome to my blog, where we dive into the exciting and ever-evolving world of data engineering, machine learning, and system architecture. I’m Prakritidev Verma, and I’ve spent my career tackling the complex challenges of the tech landscape.
What You’ll Find Here
In this space, I share my experiences, insights, and tips on a variety of topics that I’m passionate about:
- Programming Mastery: From Java to Python, Go, Lua, and JavaScript, I’ll share the tricks and best practices I’ve picked up along the way.
- Machine Learning Adventures: Whether it’s traditional ML with Scikit-learn and TensorFlow or specialized areas like Financial Machine Learning, I’ll break down the concepts and applications.
- Data Engineering: Get insights into tools like ElasticSearch, Neo4j, and MongoDB, and learn how to build robust data pipelines with frameworks like Spring Boot, Kafka, and the Elastic Stack (ELK).
- Cloud and DevOps: Dive into the world of AWS, S3, EC2, SQS, and CloudFoundry. Plus, I’ll share my favorite scripting tools like Shell Script, GNU Parallel, jq, and vim to streamline your workflow.
- Real-World Applications: I’ll discuss how these technologies come together in real-world projects, from handling millions of data events per day to optimizing search engines and creating scalable, efficient systems.
My Journey
I’ve led projects that manage massive data ingestion pipelines, crafted user-centric ranking algorithms, and built real-time analytics solutions. My work has spanned various domains, including email campaign analytics, job search engines, and financial market analysis. Along the way, I’ve learned the value of choosing the right tool for the job, balancing complexity with performance, and always pushing the envelope of what’s possible.
Why Follow This Blog?
If you’re as excited about tech as I am, you’re in the right place. Whether you’re a seasoned developer or just starting out, my goal is to provide you with valuable insights, practical tips, and a glimpse into the cutting-edge technologies shaping our future. Let’s explore, learn, and innovate together.
Topics We’ll Explore Together
- Data Pipelines and Streaming Data: Discover the ins and outs of setting up efficient data pipelines, handling streaming data, and ensuring real-time analytics.
- Graph Databases: Learn how to leverage Neo4j and other graph databases for complex relationship mapping and data lineage.
- Search and Discoverability: Dive into the mechanics of search engines, with a focus on ElasticSearch and how to optimize it for large-scale data retrieval.
- Scalable Architectures: Get a deep understanding of building scalable systems that can handle millions of requests per day without breaking a sweat.
- DevOps Best Practices: From setting up CI/CD pipelines to managing cloud infrastructure, I’ll share the tools and techniques that keep everything running smoothly.
Connect ?
You can also connect with me on LinkedIn and check out my projects on GitHub.
Stick around, and let’s geek out over the amazing possibilities of technology!
Resume (Because I forget things)
Due to exposure of many things, I am generally confused what am I and I have 3 different resumes tailored based on requirements. However, sometimes we all need to have a view of what exactly do we really know. Below is the exhaustive deep dive of my work experience and work exposure over the years working in the tech.
2017 (Machine Learning Era)
Graduated fresh out of college, aspiring ML engineer.
Worked @ParallelDots as an intern and used to work image processing stuff. Worked on highly imbalanced dataset classification promlem, pyTorch, VGG etc.
Worked @GOEVENTZ (Not anymore), worked on recommendation systems, cold start and content based algoithms.