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Schedule Interview NowMy name is Ahmed Faraz N. and I have over 5 years of experience in the tech industry. I specialize in the following technologies: Natural Language Processing, Deep Learning, Python, TensorFlow, Computer Vision, etc.. I hold a degree in , Bachelor of Science (BS). Some of the notable projects I've worked on include: Smart Form Filler, Music Generation, Word analogy using GloVe model and Gender Debiasing, Art generation with Neural Style Transfer using VGG network, Business Analytics using AutoML, etc.. I am based in Shahdadpur, Pakistan. I've successfully completed 10 projects while developing at Softaims.
My expertise lies in deeply understanding and optimizing solution performance. I have a proven ability to profile systems, analyze data access methods, and implement caching strategies that dramatically reduce latency and improve responsiveness under load. I turn slow systems into high-speed performers.
I focus on writing highly efficient, clean, and well-documented code that minimizes resource consumption without sacrificing functionality. This dedication to efficiency is how I contribute measurable value to Softaims' clients by reducing infrastructure costs and improving user satisfaction.
I approach every project with a critical eye for potential bottlenecks, proactively designing systems that are efficient from the ground up. I am committed to delivering software that sets the standard for speed and reliability.
Main technologies
5 years
2 Years
4 Years
4 Years
Potentially possible
Pakistan Telecommunication Limited
Auto form filler based on Computer Vision and AI Field Matching, capable of scanning form image, automatically filling it, and making available for printing. Tools and Techniques: • Android app (Clie
Generate sequence of notes of Jazz music using generative NN model in Python. - Keras - LSTMs - audio processing - notes recognition.
Solve word analogy problems such as “Man is to Woman as King is to __”. - Gender debiasing of word vectors - Cosine similarity - GloVe model.
Generate novel artistic image by merging a content image with style image. It is achieved by updating pixel values of content image and measuring similarity with the style image. - TensorFlow 1.x, VGG
On the basis of customer data, the system predicts whether or not a given customer will deposit the term. - H2O - AutoML - Data preprocessing - XGBoost - GBM - MSE ~ 0.6 - LogLoss ~ 0.19
in Data Science
2019-01-01-2021-01-01
Bachelor of Science (BS) in Software Engineering
2015-01-01-2019-01-01