https://github.com/kelixirr/neuraldemy
This is a complete machine learning and data science course that I have designed for beginners. It comes with videos as well.
https://github.com/kelixirr/neuraldemy
deep-learning machine-learning neural-network python
Last synced: 6 months ago
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This is a complete machine learning and data science course that I have designed for beginners. It comes with videos as well.
- Host: GitHub
- URL: https://github.com/kelixirr/neuraldemy
- Owner: kelixirr
- Created: 2023-03-18T13:44:34.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-22T10:35:30.000Z (over 1 year ago)
- Last Synced: 2024-05-22T13:03:11.219Z (over 1 year ago)
- Topics: deep-learning, machine-learning, neural-network, python
- Language: Jupyter Notebook
- Homepage: https://neuraldemy.com/
- Size: 10.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Neuraldemy - Machine Learning And Deep Learning Tutorials For Beginners ðŸ§
#### Master AI - One neuron at a time
Discover the world of machine learning and deep learning with our dedicated Neuraldemy repository, designed exclusively for members enrolled in our tutorials. If you're new to Neuraldemy, start your AI learning journey by [joining our platform](https://neuraldemy.com/subscription) through the Neuraldemy Subscription.
**Unlock The Full Potential:**
While we offer these resources for free, consider becoming a paid subscriber for added benefits. Subscribers enjoy the privilege of asking questions, exploring in-depth concepts, and demystifying the mathematics behind these AI black boxes.
Join Neuraldemy today and become part of a vibrant community passionate about AI education and exploration.
👉 [Neuraldemy Platform](https://neuraldemy.com/)
## How To Use It:
This repository contains all our free resources related to machine learning created and maintained by Amritesh Kumar. The best way to navigate through these resources is to follow our tutorial available on our website, but they can still be used independently. This repository contains:
1. **ML Tools**: A folder containing all the tools you need to get started in machine learning or deep learning. This section is entirely free, and you must know these libraries to get started in ML.
2. **ML Tutorial**: This folder contains all our free resources related to tutorials (only the practical section, not theory). You can still use them based on your knowledge.
3. **ML Projects**: This folder has some ML projects that you can use to practice and learn ML. However, most of the projects are in another repository (AI Projects).
### Premium Tutorials
1. https://neuraldemy.com/singular-value-decomposition/
2. https://neuraldemy.com/in-depth-linear-regression-concept-and-application/
3. https://neuraldemy.com/principal-components-analysis/
4. https://neuraldemy.com/linear-discriminant-analysis/
5. https://neuraldemy.com/in-depth-naive-bayes-concept-and-application/
6. https://neuraldemy.com/in-depth-logistic-regression/
7. https://neuraldemy.com/support-vector-machines/
8. https://neuraldemy.com/in-depth-decision-trees-concept-and-application/
9. https://neuraldemy.com/stochastic-gradient-descent/
10. https://neuraldemy.com/in-depth-random-forests-ensemble-learning-concept-and-application/
11. https://neuraldemy.com/nearest-neighbors-concept/
12. https://neuraldemy.com/shop/clustering-and-outlier-detection/
13. https://neuraldemy.com/gaussian-mixture-models/
14. https://neuraldemy.com/deep-learning-introduction-to-anns/
15. https://neuraldemy.com/convolutional-neural-networks-cnns/
NLP tutorial is coming soon 🔥
### ML Projects
Practice machine learning and build a portfolio: https://github.com/kelixirr/AI-Projects
### Ask Doubts
If you are stuck or want to ask something, feel free to visit our community https://neuraldemy.com/community/ and raise your query in the forum.
### Extra Resources
Learn The Basics of Tensorflow 2: https://ryancheunggit.gitbooks.io/tfbook/content/
Machine learning papers: https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap and https://github.com/terryum/awesome-deep-learning-papers