Jupyter Notebook Tutorial

Open-source Jupyter Notebook projects categorized as Tutorial Edit details

Top 23 Jupyter Notebook Tutorial Projects

  • TensorFlow-Examples

    TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

  • digital_video_introduction

    A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding).

    Project mention: Ask HN: How can I learn about video encoding, h.264, ffmpeg, etc. | news.ycombinator.com | 2022-04-01

    A good high-level breakdown of H.264: https://sidbala.com/h-264-is-magic/

    Associated HN post (although there have been a few): https://news.ycombinator.com/item?id=30710574

    More technical: https://github.com/leandromoreira/digital_video_introduction...

  • SonarLint

    Deliver Cleaner and Safer Code - Right in Your IDE of Choice!. SonarLint is a free and open source IDE extension that identifies and catches bugs and vulnerabilities as you code, directly in the IDE. Install from your favorite IDE marketplace today.

  • TensorFlow-Tutorials

    TensorFlow Tutorials with YouTube Videos

  • computervision-recipes

    Best Practices, code samples, and documentation for Computer Vision.

    Project mention: How is accuracy calculated in multi label classification | reddit.com/r/MLQuestions | 2022-01-31
  • pandas_exercises

    Practice your pandas skills!

    Project mention: [NBS Accountancy] Ranking and Tiering every core modules with description)! Hope this will be fun read for the current/past Accountancy students, and helpful for incoming batch of Accountancy students :)) | reddit.com/r/NTU | 2022-05-31

    Tips: For quiz 1, I used this whereas for quiz 2, I used this to revise. I cannot conclude whether they really helped in the end since the quiz results aren't released, but managed to nab an A for this mod so there's that.

  • pytorch-seq2seq

    Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

    Project mention: [D] How to truly understand attention mechanism in transformers? | reddit.com/r/MachineLearning | 2021-10-29
  • pytorch-sentiment-analysis

    Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

    Project mention: Ich habe einen Bot gebastelt für Ovalwichs | reddit.com/r/ovalwichs | 2022-03-25

    z.B. https://github.com/bentrevett/pytorch-sentiment-analysis

  • JetBrains

    Developer Ecosystem Survey 2022. Take part in the Developer Ecosystem Survey 2022 by JetBrains and get a chance to win a Macbook, a Nvidia graphics card, or other prizes. We’ll create an infographic full of stats, and you’ll get personalized results so you can compare yourself with other developers.

  • 100-plus-Python-programming-exercises-extended

    The repository is about 100+ python programming exercise problem discussed, explained, and solved in different ways

  • qiskit-tutorials

    A collection of Jupyter notebooks showing how to use the Qiskit SDK

    Project mention: IBM Certified Associate Developer - Is the study guide enough? | reddit.com/r/QuantumComputing | 2021-11-13

    I've completed my exam about a month ago. From official resources, I recommend this https://github.com/Qiskit/qiskit-tutorials/tree/master/tutorials/circuits

  • JuliaTutorials

    Learn Julia via interactive tutorials!

    Project mention: Looking for an Open Source Project? Try Julia. | dev.to | 2021-10-04

    Additionally, there are tons of resources available to learn Julia. Visit https://julialang.org/learning/ for a complete list of educational resources. The resources are categorized by learning style.

  • reinforcement_learning_course_materials

    Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University

    Project mention: PGWAD pool updates and some learning materials | reddit.com/r/CardanoStakePools | 2022-03-07
  • JustEnoughScalaForSpark

    A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.

  • intro-to-python

    An intro to Python & programming for wanna-be data scientists

  • pytorch-image-classification

    Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

    Project mention: neural networks project | reddit.com/r/learnmachinelearning | 2022-03-29

    https://github.com/bentrevett/pytorch-image-classification You can find plethora of options like the one above that I have sent, just google it, After mnist usually people go for image classification for differentiating between cats and dogs

  • Julia-DataFrames-Tutorial

    A tutorial on Julia DataFrames package

    Project mention: How do I access a specific column/row based on the column name and/or row value with an indexed table? | reddit.com/r/Julia | 2021-08-15

    Take a look at the these notebooks: https://github.com/bkamins/Julia-DataFrames-Tutorial

  • psi4numpy

    Combining Psi4 and Numpy for education and development.

  • feature-engineering-tutorials

    Data Science Feature Engineering and Selection Tutorials

    Project mention: How to balance multiple time series data? | reddit.com/r/datascience | 2022-03-08

    I’ve actually solved a similar problem several times in a variety of settings. I’ve had success with boosted trees and feature engineering on the sensor readings over time. I treat each reading as an observation and set the target to be the value I want to forecast (e.g. one hour ahead, the sum over the next day, the value at the same time the next day). There was a recent paper that compared boosted trees to deep learning techniques and found the boosted trees performed really well. Next, I perform feature engineering to aggregate the data up to the current time. These features will include the current value, lagged values over multiple observations for that sensor, more complicated features from moving statistics over different time scales, etc. I actually wrote a blog about creating these features using the open-source package RasgoQL and have similar types of features shared in the open-source repository here. I have also had success creating these sorts of historical features using the tsfresh package. Finally, when evaluating the forecast, use a time based split so earlier data is used to train the model and later data to evaluate the model.

  • Anomaly_Detection_Tuto

    Anomaly detection tutorial on univariate time series with an auto-encoder

  • z3_tutorial

    Jupyter notebooks for tutorial on the Z3 SMT solver

  • Deep-Learning

    In-depth tutorials on deep learning. The first one is about image colorization using GANs (Generative Adversarial Nets).

  • ml-pipeline-engineering

    Best practices for engineering ML pipelines.

    Project mention: Engineering ML Pipelines - Part 2 of 3 | reddit.com/r/mlops | 2021-07-27

    Part One was all about getting setup and ready for the main event that is Part Two - developing the pipeline:

  • bigpython

    Source code for Big Python tutorials on YouTube

  • Understanding_the_EM_Algorithm

    Codes for my blog post "Understanding the EM Algorithm" https://mistylight.github.io/posts/20115/

    Project mention: [D] My new blog post "Understanding the EM Algorithm" | reddit.com/r/MachineLearning | 2021-10-30

    The EM algorithm is very straightforward to understand with one or two proof-of-concept examples. However, if you really want to understand how it works, it may take a while to walk through the math. The purpose of this article is to establish a good intuition for you, while also provide the mathematical proofs for interested readers. The codes for all the examples mentioned in this article can be found at https://github.com/mistylight/Understanding_the_EM_Algorithm.

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2022-05-31.

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