| 1. Gridspec and other functions#221.mp4 | 76 MB | ||
| 1. Gridspec and other functions#221.srt | 15.5 KB | ||
| 1. Introduction.mp4 | 14.7 MB | ||
| 1. Introduction.srt | 3.1 KB | ||
| 1.1 222_new.original | 1 KB | ||
| 1.2 222_new.original | 1 KB | ||
| 10. UCSSL Cont.mp4 | 81.8 MB | ||
| 10. UCSSL Cont.srt | 10.8 KB | ||
| 10.1 Untitled16.py | 2.7 KB | ||
| 11. DBSCAN-1.mp4 | 79 MB | ||
| 11. DBSCAN-1.srt | 13.2 KB | ||
| 11.1 Untitled16.py | 4.5 KB | ||
| 12. DBSCAN-2.mp4 | 62.1 MB | ||
| 12. DBSCAN-2.srt | 10.2 KB | ||
| 12.1 Untitled16.py | 4.9 KB | ||
| 2. Gridspec using Subplotspec#222.mp4 | 66.8 MB | ||
| 2. Gridspec using Subplotspec#222.srt | 13.6 KB | ||
| 2. K means clustering.mp4 | 145.7 MB | ||
| 2. K means clustering.srt | 24.6 KB | ||
| 2.1 222_new.original | 1 KB | ||
| 3. K Means clustering -cont.mp4 | 49.1 MB | ||
| 3. K Means clustering -cont.srt | 4.4 KB | ||
| 4. K Means Clustering finishing.mp4 | 49.2 MB | ||
| 4. K Means Clustering finishing.srt | 7 KB | ||
| 4.1 235.py | 2.8 KB | ||
| 5. hierarchical clustering.mp4 | 88.2 MB | ||
| 5. hierarchical clustering.srt | 14.1 KB | ||
| 5.1 237.py | 921.6 B | ||
| 6. More Highlight-Unsupervised-Clustering -Kmeans.mp4 | 90 MB | ||
| 6. More Highlight-Unsupervised-Clustering -Kmeans.srt | 14 KB | ||
| 6.1 239.py | 716.8 B | ||
| 7. mean shift from scratch.mp4 | 159.9 MB | ||
| 7. mean shift from scratch.srt | 16.5 KB | ||
| 7.1 240.py | 1.8 KB | ||
| 8. Using clustering with preprocessing.mp4 | 138.3 MB | ||
| 8. Using clustering with preprocessing.srt | 16.3 KB | ||
| 8.1 240.py | 512 B | ||
| 9. Using clustering for semi supervised learning.mp4 | 141.8 MB | ||
| 9. Using clustering for semi supervised learning.srt | 21 KB | ||
| 9.1 clustering for Semi Supervised Learning.txt | 2.1 KB | ||
| 9.2 Untitled16-Copy1.py | 1.5 KB | ||
| Bonus Resources.txt | 307.2 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 43 total files | |||
Enticing random Pearls of Machine Learning-The gist of 21-22
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.21 GB | Duration: 4h 4m
Key revision points -Handpicked points of Concepts ,tools and techniques to build intelligent systems (python framework)
What you'll learn
Have a fundamental understanding of the Python programming language.
Acquire the pre-requisite Python skills to move into specific branches - Machine Learning, Data Science, etc.
Understand how to create your own Python programs.
Understand both Python 3.
Description
What is machine learning?
Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.
Recommendation engines are a common use case for machine learning. Other popular uses include fraud detection, spam filtering, malware threat detection, business process automation (BPA) and predictive maintenance.
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