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6. Model Training and Evaluation.mp4 153.2 MB
5. Feature Engineering and Selection.mp4 125.2 MB
11. Summary.mp4 112.7 MB
4. Data Import and Validation.mp4 92.3 MB
2. Setup.mp4 71.6 MB
10. Using Multiple Features.mp4 48.5 MB
3. Exploring Your Data.mp4 44.8 MB
8. Data Sampling.mp4 41.2 MB
7. Data Normalization.mp4 39.6 MB
9. Deep Learning.mp4 26.2 MB
1. Introduction.mp4 19.9 MB
gcp-building-a-ml-model-main.zip 245.6 kB
6. Model Training and Evaluation.srt 19.6 kB
car-data.csv 18.1 kB
5. Feature Engineering and Selection.srt 14.6 kB
4. Data Import and Validation.srt 11.0 kB
2. Setup.srt 5.9 kB
8. Data Sampling.srt 4.3 kB
7. Data Normalization.srt 4.3 kB
10. Using Multiple Features.srt 4.0 kB

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【影视】 [SHIZA Project] Machine-Doll wa Kizutsukanai TV [MVO] [HDTVRip]

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【影视】 [FreeCourseSite.com] Udemy - Machine Learning Essentials (2023) - Master core ML concepts

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5. Logistic Regression/3. Hypothesis Function.mp4 285.5 MB
3. Linear Regression/7. Gradient Descent Code.mp4 284.5 MB
19. Ensemble Learning Boosting/5. GBDT Algorithm.mp4 257.1 MB
4. Linear Regression - Multiple Features/8. Code 04 - Gradient Computation.mp4 233.1 MB
12. Naive Bayes Algorithm/7. Understanding Golf Dataset.mp4 229.4 MB
19. Ensemble Learning Boosting/3. Boosting Mathematical Formulation.mp4 221.8 MB
13. Multinomial Naive Bayes/4. Bernoulli Naive Bayes.mp4 214.7 MB
15. Decision Trees/5. Information Gain.mp4 209.2 MB
2. Supervised vs Unsupervised Learning/2. Supervised Learning Example.mp4 207.7 MB
9. PROJECT - Face Recognition/7. Face Recognition 01 - Data Collection.mp4 207.6 MB
3. Linear Regression/4. Loss Error Function.mp4 204.9 MB
12. Naive Bayes Algorithm/6. Computing Likelihood.mp4 202.5 MB
13. Multinomial Naive Bayes/3. Multinomial Naive Bayes Example.mp4 187.9 MB
7. Principal Component Analysis (PCA)/3. Maximising Variance.mp4 186.6 MB
3. Linear Regression/2. Notation.mp4 179.7 MB
3. Linear Regression/11. Code 02 - Data Normalisation.mp4 179.2 MB
12. Naive Bayes Algorithm/10. CODE - Likelihood.mp4 174.6 MB
12. Naive Bayes Algorithm/5. Naive Bayes for Text Classification.mp4 168.5 MB
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19. Ensemble Learning Boosting/4. Concept of Pseudo Residuals.mp4 160.2 MB

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【影视】 [GigaCourse.Com] Udemy - Python for Data Science & Machine Learning from A-Z

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19. PCA/7. PCA - Image Compression.mp4 262.1 MB
16. Ensemble Learning and Random Forests/6. Implementing Random Forests from scratch Part 1.mp4 212.4 MB
15. Decision Trees/7. ID3 - Putting Everything Together.mp4 191.3 MB
14. K Nearest Neighbors/3. EDA on Iris Dataset.mp4 169.7 MB
15. Decision Trees/3. What is Entropy and Information Gain.mp4 142.7 MB
19. PCA/9. PCA - Biplot and the Screen Plot.mp4 142.2 MB
1. Introduction/6. How To Get a Data Science Job.mp4 137.6 MB
1. Introduction/5. What is a Data Scientist.mp4 133.7 MB
17. Support Vector Machines/6. SVM - Kernel Types.mp4 132.5 MB
15. Decision Trees/2. EDA on Adult Dataset.mp4 129.2 MB
15. Decision Trees/8. Evaluating our ID3 implementation.mp4 127.9 MB
19. PCA/8. PCA Data Preprocessing.mp4 126.3 MB
15. Decision Trees/13. Pruning.mp4 118.5 MB
17. Support Vector Machines/8. SVM with Non-linear Dataset.mp4 117.0 MB
13. Linear and Logistic Regression/3. Linear Regression + Correlation Methods.mp4 115.7 MB
18. K-means/3. Representing Clusters.mp4 114.9 MB
3. Python For Data Science/15. Python Dictionaries.mp4 109.2 MB
17. Support Vector Machines/7. SVM with Linear Dataset (Iris).mp4 106.5 MB
18. K-means/1. Unsupervised Machine Learning Intro.mp4 105.8 MB
9. Machine Learning/1. Introduction To Machine Learning.mp4 103.5 MB

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【影视】 Python Machine Learning and Data science Course 2023

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[TutsNode.net] - Python Machine Learning and Data science Course 2023/4 - NumPy and Data Science/18 - Numpy 4.mp4 195.2 MB
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[TutsNode.net] - Python Machine Learning and Data science Course 2023/5 - Machine Learning Models/34 - Model 4.mp4 81.1 MB
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【影视】 [ DevCourseWeb.com ] Udemy - Master Machine Learning with Practical Case Studies

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【影视】 [ DevCourseWeb.com ] Udemy - Data Science Case Study - Real-World Machine Learning Project

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