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文件列表
4. Distributions/29. Practical Example Distributions.mp4
165.1 MB
3. Bayesian Inference/22. Practical Example Bayesian Inference.mp4
152.0 MB
2. Combinatorics/20. Practical Example Combinatorics.mp4
140.9 MB
5. Tie-ins to Other Fields/1. Tie-ins to Finance.mp4
103.6 MB
4. Distributions/3. What are the two main types of distributions based on the type of data we have.mp4
96.1 MB
1. Introduction to Probability/2. What is the probability formula.mp4
90.0 MB
4. Distributions/15. What is a Continuous Distribution.mp4
88.2 MB
5. Tie-ins to Other Fields/2. Tie-ins to Statistics.mp4
80.9 MB
1. Introduction to Probability/4. How to compute expected values.mp4
79.4 MB
4. Distributions/1. What is a probability distribution.mp4
76.9 MB
4. Distributions/11. What is the Binomial Distribution.mp4
72.2 MB
5. Tie-ins to Other Fields/3. Tie-ins to Data Science.mp4
66.5 MB
1. Introduction to Probability/6. What is a probability frequency distribution.mp4
64.6 MB
1. Introduction to Probability/8. What is a complement.mp4
62.0 MB
2. Combinatorics/11. What are combinations and how are they similar to variations.mp4
60.1 MB
3. Bayesian Inference/7. What is the union of sets A and B.mp4
60.0 MB
4. Distributions/13. What is the Poisson Distribution.mp4
58.5 MB
1. Introduction to Probability/1. What does the course cover.mp4
55.2 MB
3. Bayesian Inference/20. When do we use Bayes' Theorem in Real Life.mp4
52.4 MB
4. Distributions/27. What is the Logistic Distribution.mp4
52.4 MB
3. Bayesian Inference/18. How do we derive the Multiplication Rule formula.mp4
51.4 MB
4. Distributions/19. Standardizing a Normal Distribution.mp4
50.2 MB
3. Bayesian Inference/3. What are the different ways two events can interact with one another.mp4
49.7 MB
3. Bayesian Inference/13. What is the difference between P(AB) and P(BA).mp4
48.1 MB
3. Bayesian Inference/1. What is a set.mp4
47.7 MB
4. Distributions/17. What is a Normal Distribution.mp4
45.9 MB
2. Combinatorics/9. What if we couldn't use certain values more than once.mp4
45.2 MB
2. Combinatorics/3. When do we use Permutations.mp4
43.5 MB
2. Combinatorics/17. What is the chance of a single ticket winning the lottery.mp4
43.3 MB
2. Combinatorics/13. What is symmetry in Combinations.mp4
42.2 MB
4. Distributions/25. What is an Exponential Distribution.mp4
42.1 MB
2. Combinatorics/19. A Summary of Combinatorics.mp4
40.2 MB
2. Combinatorics/5. Solving Factorials.mp4
37.9 MB
3. Bayesian Inference/15. Conditional Probability in Real-Life.mp4
36.6 MB
3. Bayesian Inference/11. What does it mean to for two events to be dependent.mp4
36.5 MB
4. Distributions/9. What is the Bernoulli Distribution.mp4
35.8 MB
2. Combinatorics/7. Why can we use certain values more than once.mp4
35.6 MB
2. Combinatorics/15. How do we combine combinations of events with separate sample spaces.mp4
34.6 MB
3. Bayesian Inference/16. How do we apply the additive rule.mp4
28.3 MB
3. Bayesian Inference/5. What is the intersection of sets A and B.mp4
28.2 MB
4. Distributions/23. What is a Chi Squared Distribution.mp4
27.6 MB
3. Bayesian Inference/9. Are all complements mutually exclusive.mp4
26.6 MB
4. Distributions/7. What is the Discrete Uniform Distribution.mp4
25.6 MB
4. Distributions/5. Discrete Distributions and their characteristics..mp4
23.8 MB
4. Distributions/21. What is a Student's T Distribution.mp4
23.1 MB
2. Combinatorics/1. Why are combinatorics useful.mp4
17.0 MB
3. Bayesian Inference/22.1 CDS_2017-2018 Hamilton_jp2.zip
13.8 MB
4. Distributions/29.3 FIFA19 (post).csv
9.1 MB
4. Distributions/29.4 FIFA19.csv
9.1 MB
4. Distributions/1.1 Course Notes - Probability Distributions_jp2.zip
8.2 MB
1. Introduction to Probability/2.1 Section 1 Course Notes_jp2.zip
4.1 MB
4. Distributions/15.1 Solving Integrals_jp2.zip
3.0 MB
3. Bayesian Inference/1.1 Section 3 Course Notes_jp2.zip
2.5 MB
2. Combinatorics/20.2 Additional Exercises Combinatorics Solutions_jp2.zip
2.5 MB
2. Combinatorics/11.1 Combinations With Repetition_jp2.zip
2.3 MB
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2. Combinatorics/1.1 Section 2 Course Notes_jp2.zip
1.4 MB
4. Distributions/17.1 Normal Distribution - Expected Value and Variance_jp2.zip
1.3 MB
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3. Bayesian Inference/1.1 Section 3 Course Notes.pdf
395.3 kB
5. Tie-ins to Other Fields/1.1 Probability in Finance Homework_jp2.zip
390.6 kB
1. Introduction to Probability/2.1 Section 1 Course Notes.pdf
380.0 kB
2. Combinatorics/13.1 Symmetry Explained_jp2.zip
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4. Distributions/15.1 Solving Integrals.pdf
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2. Combinatorics/20.2 Additional Exercises Combinatorics Solutions.pdf
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2. Combinatorics/1.1 Section 2 Course Notes.pdf
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2. Combinatorics/20.1 Additional Exercises Combinatorics.pdf
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3. Bayesian Inference/22.1 CDS_2017-2018 Hamilton_djvu.txt
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