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种子名称： udemy-probability-for-statistics-and-data-science
文件类型： 视频
文件数目： 46个文件
文件大小： 2.46 GB
收录时间： 2021-8-3 21:51
已经下载： 3次
资源热度： 147
最近下载： 2024-5-2 13:43

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udemy-probability-for-statistics-and-data-science.torrent

1. Introduction to Probability/1. What does the course cover.mp452.68MB

1. Introduction to Probability/2. What is the probability formula.mp485.88MB

1. Introduction to Probability/4. How to compute expected values.mp475.74MB

1. Introduction to Probability/6. What is a probability frequency distribution.mp461.61MB

1. Introduction to Probability/8. What is a complement.mp459.11MB

2. Combinatorics/1. Why are combinatorics useful.mp416.17MB

2. Combinatorics/11. What are combinations and how are they similar to variations.mp457.3MB

2. Combinatorics/13. What is symmetry in Combinations.mp440.27MB

2. Combinatorics/15. How do we combine combinations of events with separate sample spaces.mp433.04MB

2. Combinatorics/17. What is the chance of a single ticket winning the lottery.mp441.32MB

2. Combinatorics/19. A Summary of Combinatorics.mp438.31MB

2. Combinatorics/20. Practical Example Combinatorics.mp4134.38MB

2. Combinatorics/3. When do we use Permutations.mp441.49MB

2. Combinatorics/5. Solving Factorials.mp436.13MB

2. Combinatorics/7. Why can we use certain values more than once.mp433.97MB

2. Combinatorics/9. What if we couldn't use certain values more than once.mp443.08MB

3. Bayesian Inference/1. What is a set.mp445.52MB

3. Bayesian Inference/11. What does it mean to for two events to be dependent.mp434.78MB

3. Bayesian Inference/13. What is the difference between P(AB) and P(BA).mp445.84MB

3. Bayesian Inference/15. Conditional Probability in Real-Life.mp434.91MB

3. Bayesian Inference/16. How do we apply the additive rule.mp426.95MB

3. Bayesian Inference/18. How do we derive the Multiplication Rule formula.mp449.06MB

3. Bayesian Inference/20. When do we use Bayes' Theorem in Real Life.mp450MB

3. Bayesian Inference/22. Practical Example Bayesian Inference.mp4144.96MB

3. Bayesian Inference/3. What are the different ways two events can interact with one another.mp447.44MB

3. Bayesian Inference/5. What is the intersection of sets A and B.mp426.93MB

3. Bayesian Inference/7. What is the union of sets A and B.mp457.21MB

3. Bayesian Inference/9. Are all complements mutually exclusive.mp425.4MB

4. Distributions/1. What is a probability distribution.mp473.36MB

4. Distributions/11. What is the Binomial Distribution.mp468.89MB

4. Distributions/13. What is the Poisson Distribution.mp455.8MB

4. Distributions/15. What is a Continuous Distribution.mp484.16MB

4. Distributions/17. What is a Normal Distribution.mp443.75MB

4. Distributions/19. Standardizing a Normal Distribution.mp447.92MB

4. Distributions/21. What is a Student's T Distribution.mp422MB

4. Distributions/23. What is a Chi Squared Distribution.mp426.37MB

4. Distributions/25. What is an Exponential Distribution.mp440.17MB

4. Distributions/27. What is the Logistic Distribution.mp449.98MB

4. Distributions/29. Practical Example Distributions.mp4157.47MB

4. Distributions/3. What are the two main types of distributions based on the type of data we have.mp491.61MB

4. Distributions/5. Discrete Distributions and their characteristics..mp422.68MB

4. Distributions/7. What is the Discrete Uniform Distribution.mp424.4MB

4. Distributions/9. What is the Bernoulli Distribution.mp434.15MB

5. Tie-ins to Other Fields/1. Tie-ins to Finance.mp498.83MB

5. Tie-ins to Other Fields/2. Tie-ins to Statistics.mp477.19MB

5. Tie-ins to Other Fields/3. Tie-ins to Data Science.mp463.46MB