Learn Machine Learning
through code
Implement 1,300+ algorithms from scratch, from foundational ML to CUDA kernels, with the math, visualizations, and research papers behind them.
Loss surface
step 0|loss 24.250
- is correct
- every step
- converges
Trusted by users from
The complete ML engineering platform
loss L(w)|rolling down the gradient
import numpy as np
def linear_regression(X, y, lr=0.01):
w, b = 0.0, 0.0
for _ in range(100):
err = w * X + b - y
w -= lr * (err * X).mean()
b -= lr * err.mean()
return w, bSystems and GPU programming
AI Research Papers
Agentic Systems
Mathematics for ML
ML system design
Try the problems
Direction reveals how similar two vectors are. Change the angle and compare their alignment.
A single function decides what a neuron passes on. Change the input and follow the output.
Rows become columns while each value stays the same. Select a cell and follow its new position.
Edit a value or select a transposed cell to follow its new position.
What learners are saying
50,000+
learners worldwide
1Million+
code submissions
1,000+
problems to solve









Plans
Free
$0forever
Start building your ML foundations
- Unlimited code submissions
- 500+ problems
- 35 CUDA / GPU kernel problems
- Interactive visualizations
- Theory content per problem
- 13 research paper implementations
- ML Math blogs
- Community Discord access
- Structured study plans
- Real-time interview mock assessments
- ML System Design problems
Pro
$12/month
or $100/yr · save 31%
- Everything in Free
- Structured roadmap study plansPandas, NumPy, PyTorch, SQL FoundationsLinear Algebra, Probability, Calculus, OptimizationML, DL, NLP, RL, CV specializations
- 500+ quiz questions across 12 modules
- Real-time interview mock assessmentsData Scientist, ML Engineer, AI EngineerResearch Engineer, GPU and Performance
- Priority support
- ML System Design problems
- Modern LLM architectures like GPT2, DeepSeek
Plus
$20/month
or $168/yr · save 30%
- Everything in Pro
- Implement modern LLM architectures like GPT-2, DeepSeek etc in PyTorch
- ML System Design problems
- Interactive design canvas
- FAANG-styled system design scenarios
Questions, answered
Is TensorTonic free to use?
TensorTonic has more than 500 problems, CUDA and GPU kernel exercises, 13 research paper implementations, and the full ML Math library completely free. Premium plans add structured study plan roadmaps, ML system design, and interview preparation.
Stop watching.
Start building.
Don't just watch ML theory. Implement it yourself, one algorithm at a time, and understand it in depth.