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himanshuy08/README.md
Terminal animation

model_summary()

$ cat model_summary.txt
Model:        Himanshu Yadav
Degree:       M.Tech, Data Analytics
Objective:    minimize(ignorance) subject to time_constraints
Status:       active

checkpoints.log

$ tail -f checkpoints.log
[ckpt] first line of code        -> curiosity initialized
[ckpt] DSA grind started         -> pattern recognition improving
[ckpt] ML fundamentals learned   -> gradient pointing downhill
[ckpt] built with FastAPI/Flask  -> backend layer added
[ckpt] NLP / LLMs started        -> attention weights shifting
[ckpt] M.Tech, Data Analytics    -> batch size: real-world problems

architecture.summary()

$ python model.py --summary
Input Layer        →  Curiosity, DSA practice
Hidden Layer 1      →  Python, C++
Hidden Layer 2      →  PyTorch, TensorFlow
Hidden Layer 3      →  FastAPI, React
Regularization      →  Docker, Git
Output Layer        →  Working software
Loss Function       →  distance(current_skill, next_problem)


hyperparameters.yaml

$ cat hyperparameters.yaml
currently_exploring:
  - machine_learning_and_deep_learning_fundamentals
  - natural_language_processing_and_llms
  - python_backend_frameworks: [fastapi, flask]
  - leetcode_and_algorithms

open_to:
  - collaborations
  - internships
  - knowledge_exchange

eval_metrics()


inference.log

> model.predict(next_5_years)
Output: still computing — check back after the next commit
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