Mastering Data Science, Machine Learning, and AI --> [ DevCourseWeb ]

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Torrent Hash :	673F4D28988E3B9899456FBF3BBEE63398B8A1FC
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Torrent Size :	732.4 MB

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Torrent File Content (43 files)

[ DevCourseWeb.com ] Udemy - Mastering Data Science, Machine Learning, and AI
Get Bonus Downloads Here.url -

182 bytes

~Get Your Files Here !
1. Introduction to Data Science/1. What is data science and why is it important.mp4 -

14.07 MB

1. Introduction to Data Science/2. The process of data science and its different stages.mp4 -

27.29 MB

1. Introduction to Data Science/3. Different fields that use data science and examples of real-world applications.mp4 -

26.4 MB

1. Introduction to Data Science/4. Overview of the tools and techniques used in data science.mp4 -

25.08 MB

10. Ethics and Bias in AI/1. The impact of AI on society and ethics.mp4 -

28.33 MB

10. Ethics and Bias in AI/2. Bias in AI and its implications.mp4 -

15.75 MB

10. Ethics and Bias in AI/3. Fairness and accountability in AI.mp4 -

13.97 MB

10. Ethics and Bias in AI/4. Best practices for avoiding bias in AI models.mp4 -

17.93 MB

11. Conclusion/1. Recap of key concepts and takeaways.mp4 -

13.05 MB

11. Conclusion/2. Opportunities and challenges in data science, machine learning, and AI.mp4 -

28.22 MB

11. Conclusion/3. Suggestions for further learning and resources.mp4 -

23.21 MB

11. Conclusion/4. Quiz.html -

197 bytes

2. Data Collection and Preprocessing/1. Sources of data and methods of collecting data.mp4 -

23.44 MB

2. Data Collection and Preprocessing/2. Understanding and cleaning data.mp4 -

21.82 MB

2. Data Collection and Preprocessing/3. Dealing with missing and duplicate values.mp4 -

15.53 MB

2. Data Collection and Preprocessing/4. Feature engineering and selection.mp4 -

20.74 MB

3. Exploratory Data Analysis/1. Univariate and multivariate analysis.mp4 -

22.77 MB

3. Exploratory Data Analysis/2. Data visualization techniques.mp4 -

18.27 MB

3. Exploratory Data Analysis/3. Identifying relationships and patterns in data.mp4 -

22.16 MB

4. Statistical Modeling/1. Overview of statistics and probability.mp4 -

25.05 MB

4. Statistical Modeling/2. Introduction to regression and classification models.mp4 -

9.09 MB

4. Statistical Modeling/3. Overfitting and underfitting.mp4 -

16.18 MB

4. Statistical Modeling/4. Model evaluation and selection.mp4 -

18.52 MB

5. Machine Learning/1. Introduction to machine learning.mp4 -

14.49 MB

5. Machine Learning/2. Different types of machine learning algorithms.mp4 -

24.39 MB

5. Machine Learning/3. Overfitting and regularization.mp4 -

9.46 MB

5. Machine Learning/4. Feature scaling and normalization.mp4 -

9.89 MB

6. Supervised Learning/1. Linear regression and logistic regression.mp4 -

13.76 MB

6. Supervised Learning/2. Decision trees and random forests.mp4 -

14.4 MB

6. Supervised Learning/3. Support vector machines.mp4 -

9.84 MB

6. Supervised Learning/4. Neural networks and deep learning.mp4 -

14.05 MB

7. Unsupervised Learning/1. Clustering algorithms.mp4 -

17.04 MB

7. Unsupervised Learning/2. Dimensionality reduction.mp4 -

19.51 MB

7. Unsupervised Learning/3. Anomaly detection.mp4 -

18.11 MB

8. Reinforcement Learning/1. Markov decision processes.mp4 -

16.98 MB

8. Reinforcement Learning/2. Q-learning.mp4 -

11.36 MB

8. Reinforcement Learning/3. Policy gradient methods.mp4 -

19.28 MB

9. Artificial Intelligence/1. Definition and history of artificial intelligence.mp4 -

18.67 MB

9. Artificial Intelligence/2. Types of artificial intelligence and their applications.mp4 -

25.71 MB

9. Artificial Intelligence/3. Natural language processing and computer vision.mp4 -

10.99 MB

9. Artificial Intelligence/4. Overview of deep learning and its applications.mp4 -

17.64 MB

Bonus Resources.txt -

386 bytes

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