towardsai/tutorials

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

Tutorials

Please know that only the code contained in this repository is under the MIT license found at "LICENSE." All tutorials, articles, and books listed in this repository are property of Towards AI, Inc.

Please feel free to contribute. We'll review your pull requests ad-hoc. If you'd like to work with one of our data scientists in an editorial tutorial, please reach out via [email protected] and cc: [email protected].

To contribute directly to Towards AI, check out our guidelines to get published.

Join our AI community.

If you'd like to support Towards AI, please support us by buying one of our books (listed below), sponsoring this open-source work.

Thank you for reading and for being a supporter of Towards AI!

Access any tutorial for free.

Terms | Privacy Policy

---

Machine Learning Algorithms For Beginners with Code Examples in Python

Neural Networks from Scratch with Python Code and Math in Detail— I

Building Neural Networks with Python Code and Math in Detail — II

Natural Language Processing (NLP) with Python — Tutorial

Monte Carlo Simulation An In-depth Tutorial with Python

Survival Analysis with Python Tutorial — How, What, When, and Why

Moment Generating Function for Probability Distribution with Python

Bernoulli Distribution — Probability Tutorial with Python

Recommendation System Tutorial with Python using Collaborative Filtering

Linear Algebra for Deep Learning and Machine Learning (ML) Python Tutorial

Principal Component Analysis (PCA) with Python Examples — Tutorial

Decision Trees in Machine Learning (ML) with Python Tutorial

Convolutional Neural Networks (CNNs) Tutorial with Python

Sentiment Analysis (Opinion Mining) with Python - NLP Tutorial

Gradient Descent for Machine Learning (ML) 101 with Python Tutorial

Random Number Generator Tutorial with Python

What is Deep Learning?

Genetic Algorithm (GA) Introduction with Example Code

K-Nearest Neighbors (KNN) Algorithm Tutorial — Machine Learning Basics

What is a GPU? Are GPUs Needed for Deep Learning?

Books

Descriptive Statistics for Data-driven Decision Making with Python

Sponsors

Big thank you to C4H3I LLC for sponsoring us in June, 2022!

tutorials's Issues

KNN

Minor change to coinflip logic

The plt render should be moved back one indentation, since you're really only interested in the final result and it saves you 5000 unnecessary renders

def monte_carlo(n):
results = 0
for i in range(n):
flip_result = coin_flip()
results = results + flip_result

	prob_value = results/(i+1)

	list1.append(prob_value)

plt.axhline(y=0.5, color ='r', linestyle='-')
plt.xlabel("Iterations")
plt.ylabel("Probability")
plt.plot(list1)

return results/n

Minor logic error in recommendation_system_tutorial/recommendation_system_tutorial_netflix.py

This line :
top_similar_user_ratings.extend([global_avg_rating[movie]] * (5 - len(ratings)))
should be
top_similar_user_ratings.extend([global_avg_rating[movie]] * (5 - len(top_similar_user_ratings)))

Because len(ratings) is a const large value here which is not right.

https://github.com/towardsai/tutorials/blob/master/recommendation_system_tutorial/recommendation_system_tutorial_netflix.py#L174