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26Coding & Vibe CodingFreeAge: Any

Google Colab

colab.research.google.com

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.

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