What it does This repo holds the weekly Jupyter notebooks for HSE’s Coursera NLP course. Assignments walk through classical methods and deep learning approaches using Python, TensorFlow, NLTK, Scikit-learn, and Gensim. The maintainers have clearly been burned by student setup questions: they provide a custom setup_google_colab.py script, a Docker image, and even an AWS tutorial.

The interesting bit Most course repos dump notebooks and wish you luck. This one includes a ! pkill -9 python3 tip for killing runaway Colab processes and admits that ipywidgets progress bars are broken so they ship a “simplified version.” The honesty is refreshing.

Key highlights

• Six weekly assignments plus a project and honor track, covering multilabel classification through to whatever week 4 holds
• Three execution paths: Google Colab with free GPUs, local Docker with pre-installed dependencies, or manual installation (good luck on Windows with StarSpace)
• Custom setup script per week that downloads dependencies; forgetting to uncomment your week number causes a cryptic “No module named ‘common’” error
• Tested on a Mac with 8GB RAM in Docker, though they warn some configurations may need more
• Direct GitHub integration in Colab: paste the repo URL and pick your notebook

Caveats

• Some tools like StarSpace are not Windows-compatible, so Docker is effectively mandatory for certain assignments
• Colab has known visual glitches: blinking clear_output() animations and no proper tqdm support
• The README is duplicated verbatim in the source, suggesting the repo itself is fairly static maintenance-wise

Verdict Grab this if you’re self-studying NLP and want structured assignments with realistic data wrangling. Skip it if you’re looking for a standalone library or reference implementation; this is coursework scaffolding, not a framework.