AI Tool Guides
Best for
Free Python notebooks with GPU access
Works on
Browser
Alternatives
Replit, Kaggle Notebooks
Watch out
Sessions disconnect after idle; save work frequently
What It Does
Google Colab is a free Jupyter notebook environment that runs in the cloud with access to GPUs and TPUs. You write and execute Python in your browser, with results appearing inline. It is the standard tool for data science, machine learning experiments, and AI tutorials worldwide.
Setup in 5 Minutes
and sign in with a
Google account.
- Click New Notebook.
- You now have a Python environment with NumPy, Pandas,
TensorFlow, and dozens of other libraries pre-installed.
- To enable a GPU, go to Runtime
Change runtime type T4 GPU.
Try This
In a new cell, type !pip install transformers and run it. In
the next cell, load a sentiment analysis pipeline:
from transformers import pipeline; classifier =
pipeline("sentiment-analysis"). Run
classifier("I absolutely love this book") and see the model
return a label and confidence score. You just ran a real AI model on a
cloud GPU in three lines of code.
Follow Along
Follow Along — Train a Simple Classifier.
and from sklearn.tree import DecisionTreeClassifier.
- Load the Iris dataset, split it into training and test sets with train\_test\_split(X, y, test\_size=0.3).
- Train a decision tree: clf = DecisionTreeClassifier(); clf.fit(X\_train, y\_train).
- Evaluate on the test set and plot a confusion matrix using sklearn.metrics.ConfusionMatrixDisplay.from\_estimator(clf, X\_test, y\_test).
- Print the accuracy score and try changing the tree's max\_depth parameter—observe how it affects accuracy and overfitting.
More in Coding & Vibe Coding
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Free tier24Windsurf— AI-native code editor with agentic mode
Free tier27Flask— Building lightweight Python web APIs
AI Analysis
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