colab.research.google.com · Research Platforms
Hosted Jupyter notebooks with free and paid GPU and TPU access, ideal for quick experiments and teaching.
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// guides
How to use TensorFlow in Jupyter Notebook: install it in a venv, register the kernel with ipykernel, pick it in JupyterLab or VS Code, and fix common errors.
Tinygrad vs MLX compared for Apple silicon and beyond: hardware support, lazy graphs, JIT and compile, LLM tooling, install and which framework fits your project.
Tinygrad vs PyTorch performance: when TinyJit and BEAM can outrun eager PyTorch, when torch.compile and the ecosystem win, and how to compare them fairly.
How to use TensorFlow in Python in 2026: install it in a venv, work with tensors and gradients, train a Keras model, feed data with tf.data and save it.
How to use TensorFlow with GPU in 2026: the pip [and-cuda] install on Linux and WSL2, Docker, Mac Metal, how to verify the GPU, and fixes for common errors.
TensorFlow vs PyTorch vs Keras in 2026: Keras 3 multibackend, which is easier to learn, open weight LLM ecosystem fit, and who should pick each stack.
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