I'm
Deependra Verma
AI Team Lead, Data Scientist, GenAI Engineer, AI Engineer, NLP Engineer, ML Engineer, DL Engineer, Business Analyst, Data Analyst
I'm
Know About Me
My Journey in AI Engineering, Generative AI, and Machine Learning
I am currently an AI Team Lead, specializing in Generative AI, Large Language Models (LLMs), and Large Image Models (LIM). In this role, I work on developing scalable AI solutions using cloud platforms such as AWS, Google Cloud Platform (GCP), and Microsoft Azure, while leveraging advanced GPUs from Nvidia and AMD to optimize performance and efficiency. My work focuses on deploying Generative AI models and AI-driven solutions to meet complex enterprise needs, helping organizations innovate and drive growth.
As a passionate AI engineering professional, I have a deep interest in Generative AI(GenAI), Machine Learning (ML), Deep Learning, and Data Science. My technical expertise includes Python, TensorFlow, PyTorch,, and a variety of AI frameworks, allowing me to build intelligent systems that address real-world challenges. I am dedicated to pushing the boundaries of AI technologies and am eager to continue my career in the fields of AI engineering, Machine Learning engineering, and Deep Learning engineering.
Prior to my current role, I gained valuable experience in the Ed-Tech industry, where I witnessed firsthand the transformative power of Artificial Intelligence (AI) on student learning. My time in Ed-Tech solidified my interest in applying data-driven solutions and advanced AI technologies to enhance educational experiences and optimize business processes.
My journey into technology and AI began with a strong academic foundation in Mechanical Engineering, having graduated from NIT Patna. I secured an impressive All India Rank of 950 in the GATE 2017 examination, which marked my commitment to academic excellence. I started my career as a Subject Matter Expert and teacher for JEE Main and NEET students, where I developed a passion for data analysis, Google Sheet automation, and SQL.
As I progressed, I expanded my knowledge of Operational Management and discovered the power of techniques like Linear Regression and Forecasting in business growth. This led me to explore Data Science, Machine Learning, and eventually Generative AI, where I found the perfect blend of my analytical skills and passion for creating innovative solutions.
Today, I continue to seek opportunities where I can apply my expertise in AI engineering, Generative AI, Machine Learning, and Deep Learning to drive impactful results for organizations. With a strong mathematical foundation, hands-on experience with cutting-edge AI technologies, and a passion for solving complex problems, I am ready to tackle new challenges and contribute to data-driven decision-making in the field of AI.
Python
98%
Data Science
98%
Machine Learning
98%
Deep Learning
96%
GenerativeAI, NLP, and LLMs
96%
Tableau and Power BI
94%
My Resume
My Portfolio
From Blog
The R2 score, also known as the coefficient of determination, is a statistical measure used to assess the goodness of fit of a regression model. It indicates the proportion of the variance in the dependent variable that is predictable from the independent variables. In other words, it measures how well the regression model fits the observed data.
Measures of variability or dispersion provide information about how the data points are distributed around a central tendency measure (such as the mean, median, or mode) and give an indication of the spread or extent to which the values deviate from the central value. And because of this, the dispersion is also known as a scatter, or, variation.
Data privacy is not just a buzzword — it’s a fundamental right. In a world where personal information is constantly being collected, processed, and shared, safeguarding this data against unauthorized access and misuse is critical. Whether it’s financial records, healthcare data, or user profiles, maintaining the privacy of sensitive information is essential to building trust with customers and stakeholders.
First and foremost, AWS Bedrock is all about making AI accessible to everyone. Gone are the days when you needed a team of PhDs and a hefty budget to dabble in AI. With Bedrock, you can tap into state-of-the-art models from leading AI companies with just a few clicks. It’s AI for the people, by the people.
Hypothesis testing is a fundamental tool in statistical analysis and helps researchers and analysts make objective decisions based on data. It provides a structured approach for drawing conclusions about populations from limited sample information.
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