Akshay’s Gradient

ML Coding Challenges

Hands-on coding exercises that run in parallel with your study tracks. Implement core ML components from scratch, master NumPy/PyTorch patterns, and solve algorithm problems.

Implement from Scratch

0/8 completed

Linear Regression + Gradient Descent

beginner45 min

Softmax & Cross-Entropy

beginner35 min

Self-Attention Mechanism

intermediate50 min

Multi-Head Attention

intermediate55 min

Transformer Block

advanced60 min

BPE Tokenizer

intermediate50 min

KV-Cache

advanced45 min

LoRA Layer

advanced45 min

NumPy/PyTorch Exercises

0/8 completed

Batch Matrix Multiply

beginner30 min

Custom Autograd Function

intermediate40 min

Efficient Data Loader

intermediate45 min

Mixed Precision Training Loop

advanced50 min

Gradient Accumulation

intermediate35 min

Distributed Training Script

advanced55 min

Custom LR Scheduler

intermediate35 min

Beam Search Decoding

advanced50 min

ML Algorithm Problems

0/8 completed

K-Means Clustering

beginner35 min

Decision Tree from Scratch

intermediate55 min

ANN/HNSW Index

advanced60 min

Top-k / Nucleus Sampling

intermediate35 min

Cosine Similarity Search

beginner25 min

Feature Hashing

intermediate30 min

Online Learning Update

intermediate35 min

Metrics Computation

beginner30 min