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Aspiring ML Engineer & Builder ยท IIT Patna ยท New Delhi, India
parth = {
"institute" : "IIT Patna โ Computer Science & Engineering",
"focus" : ["Machine Learning", "Deep Learning", "NLP", "Computer Vision"],
"currently" : "Building multimodal AI systems & exploring CV architectures",
"goal" : "Ship intelligent systems that solve real problems",
"fun_fact" : "I implemented backprop from scratch in NumPy before touching PyTorch"
}
๐ฌ VisionBenchBenchmarking 6 architectures on Cat vs Dog classification Systematic comparison of Logistic Regression, SVM, Custom CNN, ResNet-34, EfficientNet-B0, and ViT-Base โ from pixel vectors to attention patches.
โญ What I learned: ViT needs far more data than CNNs at this scale |
๐งฎ NeuroSketchMNIST recognition built from scratch โ zero deep learning frameworks Full training pipeline, experiment tracker, dashboard, and interactive canvas app using only NumPy. Backprop by hand.
โญ The project that taught me what autodiff actually does |
โก CortexCPPA deep learning framework written in C++ Custom tensor runtime, dynamic NN & CNN construction, shape inference, architecture validation, and forward/backward pass โ all in C++.
โญ Because understanding frameworks means building one |
๐ค RepoRelicAI-powered developer intelligence platform Deeply analyzes GitHub repositories via a multi-stage autonomous pipeline โ architecture mapping, code intelligence, and insights.
โญ Think of it as a senior engineer reviewing any repo in seconds |
๐ฌ TranscriptMindNLP-powered YouTube transcript summarization Transforms long-form transcripts into context-aware summaries using TextRank, BART, PEGASUS, and T5 โ with model comparisons.
โญ 4 summarization models, 1 clear winner (WORKING) |
๐๏ธ CortexVisionReal-time multimodal scene understanding Detection + depth estimation + segmentation + tracking + VLM fusion โ all in one pipeline for real-time environment comprehension.
โญ The most complex system I am building so far |
Languages
ML / DL
Tools & Infra