[GigaCourse.com] Udemy - Probability for Statistics and Data Science - 2048BT - 全球最新最全bt种子资源在线搜索库，实时索引全球磁力链接资源

BT种子名称

分享给好友

BT种子基本信息

种子哈希：4d9af6a693dc127d9de3f7cd2f7a245fc4d88278
文档大小：2.7 GB
文档个数：153个文档
下载次数：5478次
下载速度：极快
收录时间：2020-06-28
最近下载：2024-10-04
DMCA/屏蔽：DMCA/屏蔽

下载磁力链接

magnet:?xt=urn:btih:4D9AF6A693DC127D9DE3F7CD2F7A245FC4D88278
复制磁力链接到utorrent、Bitcomet、迅雷、115、百度网盘、PIKPAK等下载工具进行下载。

下载BT种子

磁力链接种子下载迅雷下载二维码含羞草 51品茶 91视频逼哩逼哩欲漫涩草榴社区抖阴破解版成人快手暗网禁区缅北禁地 TikTok成人版暗网解密

[GigaCourse.com] Udemy - Probability for Statistics and Data Science的二维码

文档列表

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..srt 23.8 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
4. Distributions/29.3 FIFA19.csv 9.1 MB
4. Distributions/29.6 FIFA19 (post).csv 9.1 MB
3. Bayesian Inference/22.2 CDS_2017-2018 Hamilton.pdf 865.6 kB
4. Distributions/1.1 Course Notes - Probability Distributions.pdf 458.8 kB
3. Bayesian Inference/1.1 Section 3 Course Notes.pdf 395.3 kB
1. Introduction to Probability/2.1 Section 1 Course Notes.pdf 380.0 kB
4. Distributions/15.1 Solving Integrals.pdf 352.1 kB
2. Combinatorics/20.2 Additional Exercises Combinatorics Solutions.pdf 251.6 kB
2. Combinatorics/1.1 Section 2 Course Notes.pdf 231.5 kB
2. Combinatorics/11.1 Combinations With Repetition.pdf 229.1 kB
5. Tie-ins to Other Fields/1.2 Probability in Finance Solutions.pdf 188.9 kB
4. Distributions/13.1 Poisson - Expected Value and Variance.pdf 149.5 kB
4. Distributions/17.1 Normal Distribution - Expected Value and Variance.pdf 147.5 kB
5. Tie-ins to Other Fields/1.1 Probability in Finance Homework.pdf 113.3 kB
2. Combinatorics/20.1 Additional Exercises Combinatorics.pdf 109.1 kB
2. Combinatorics/13.1 Symmetry Explained.pdf 87.1 kB
3. Bayesian Inference/22.3 Bayesian Homework - Solutions.pdf 31.1 kB
3. Bayesian Inference/22.1 Bayesian Homework .pdf 27.9 kB
4. Distributions/29.2 Daily Views (post).xlsx 20.7 kB
4. Distributions/29. Practical Example Distributions.srt 20.4 kB
3. Bayesian Inference/22. Practical Example Bayesian Inference.srt 19.8 kB
4. Distributions/29.4 Customers_Membership (post).xlsx 16.0 kB
2. Combinatorics/20. Practical Example Combinatorics.srt 14.3 kB
5. Tie-ins to Other Fields/1. Tie-ins to Finance.srt 10.1 kB
4. Distributions/29.1 Customers_Membership.xlsx 9.9 kB
4. Distributions/29.5 Daily Views.xlsx 9.8 kB
4. Distributions/3. What are the two main types of distributions based on the type of data we have.srt 9.7 kB
1. Introduction to Probability/2. What is the probability formula.srt 9.1 kB
4. Distributions/15. What is a Continuous Distribution.srt 8.9 kB
5. Tie-ins to Other Fields/2. Tie-ins to Statistics.srt 8.6 kB
4. Distributions/11. What is the Binomial Distribution.srt 8.5 kB
4. Distributions/1. What is a probability distribution.srt 7.7 kB
3. Bayesian Inference/20. When do we use Bayes' Theorem in Real Life.srt 7.4 kB
1. Introduction to Probability/8. What is a complement.srt 6.9 kB
1. Introduction to Probability/4. How to compute expected values.srt 6.8 kB
5. Tie-ins to Other Fields/3. Tie-ins to Data Science.srt 6.8 kB
4. Distributions/13. What is the Poisson Distribution.srt 6.7 kB
1. Introduction to Probability/6. What is a probability frequency distribution.srt 6.6 kB
1. Introduction to Probability/1. What does the course cover.srt 5.8 kB
2. Combinatorics/11. What are combinations and how are they similar to variations.srt 5.7 kB
3. Bayesian Inference/7. What is the union of sets A and B.srt 5.7 kB
4. Distributions/19. Standardizing a Normal Distribution.srt 5.4 kB
3. Bayesian Inference/1. What is a set.srt 5.3 kB
4. Distributions/27. What is the Logistic Distribution.srt 5.2 kB
3. Bayesian Inference/13. What is the difference between P(AB) and P(BA).srt 5.1 kB
4. Distributions/17. What is a Normal Distribution.srt 4.8 kB
3. Bayesian Inference/18. How do we derive the Multiplication Rule formula.srt 4.7 kB
2. Combinatorics/9. What if we couldn't use certain values more than once.srt 4.6 kB
3. Bayesian Inference/3. What are the different ways two events can interact with one another.srt 4.5 kB
2. Combinatorics/13. What is symmetry in Combinations.srt 4.4 kB
2. Combinatorics/17. What is the chance of a single ticket winning the lottery.srt 4.2 kB
4. Distributions/25. What is an Exponential Distribution.srt 4.2 kB
2. Combinatorics/3. When do we use Permutations.srt 4.2 kB
4. Distributions/9. What is the Bernoulli Distribution.srt 3.9 kB
2. Combinatorics/15. How do we combine combinations of events with separate sample spaces.srt 3.8 kB
2. Combinatorics/19. A Summary of Combinatorics.srt 3.8 kB
3. Bayesian Inference/15. Conditional Probability in Real-Life.srt 3.6 kB
2. Combinatorics/7. Why can we use certain values more than once.srt 3.6 kB
3. Bayesian Inference/11. What does it mean to for two events to be dependent.srt 3.5 kB
2. Combinatorics/5. Solving Factorials.srt 3.3 kB
4. Distributions/21. What is a Student's T Distribution.srt 2.9 kB
4. Distributions/23. What is a Chi Squared Distribution.srt 2.8 kB
3. Bayesian Inference/16. How do we apply the additive rule.srt 2.8 kB
4. Distributions/7. What is the Discrete Uniform Distribution.srt 2.8 kB
3. Bayesian Inference/9. Are all complements mutually exclusive.srt 2.6 kB
3. Bayesian Inference/5. What is the intersection of sets A and B.srt 2.5 kB
2. Combinatorics/1. Why are combinatorics useful.srt 1.3 kB
Readme.txt 962 Bytes
1. Introduction to Probability/3. What is the probability formula.html 154 Bytes
1. Introduction to Probability/5. How to compute expected values.html 154 Bytes
1. Introduction to Probability/7. What is a probability frequency distribution.html 154 Bytes
1. Introduction to Probability/9. What is a complement.html 154 Bytes
2. Combinatorics/10. Computing Variations without Repetition.html 154 Bytes
2. Combinatorics/12. What are combinations and how are they similar to variations.html 154 Bytes
2. Combinatorics/14. What is symmetry in Combinations.html 154 Bytes
2. Combinatorics/16. How do we combine combinations of events with separate sample spaces.html 154 Bytes
2. Combinatorics/18. What is the chance of winning the lottery.html 154 Bytes
2. Combinatorics/2. Why are combinatorics useful.html 154 Bytes
2. Combinatorics/4. When do we use Permutations.html 154 Bytes
2. Combinatorics/6. Solving Factorials.html 154 Bytes
2. Combinatorics/8. Why can we use certain values more than once.html 154 Bytes
3. Bayesian Inference/10. Are all complements mutually exclusive.html 154 Bytes
3. Bayesian Inference/12. What does it mean to for two events to be dependent.html 154 Bytes
3. Bayesian Inference/14. What is the difference between P(AB) and P(BA).html 154 Bytes
3. Bayesian Inference/17. How do we apply the additive rule.html 154 Bytes
3. Bayesian Inference/19. How do we interpret the Multiplication Rule Formula.html 154 Bytes
3. Bayesian Inference/2. What is a set.html 154 Bytes
3. Bayesian Inference/21. Bayes' Theorem.html 154 Bytes
3. Bayesian Inference/4. What are the different ways two events can interact with one another.html 154 Bytes
3. Bayesian Inference/6. What is the intersection of sets A and B.html 154 Bytes
3. Bayesian Inference/8. What is the union of sets A and B.html 154 Bytes
4. Distributions/10. What is the Bernoulli Distribution.html 154 Bytes
4. Distributions/12. What is the Binomial Distribution.html 154 Bytes
4. Distributions/14. What is the Poisson Distribution.html 154 Bytes
4. Distributions/16. What is a Continuous Distribution.html 154 Bytes
4. Distributions/18. What is a Normal Distribution.html 154 Bytes
4. Distributions/2. What is a probability distribution.html 154 Bytes
4. Distributions/20. How do we Standardize a Normal Distribution.html 154 Bytes
4. Distributions/22. What is a Student's T Distribution.html 154 Bytes
4. Distributions/24. What is a Chi-Squared Distribution.html 154 Bytes
4. Distributions/26. What is an Exponential Distribution.html 154 Bytes
4. Distributions/28. What is a Logistic Distribution.html 154 Bytes
4. Distributions/4. What are the two main types of distributions based on the type of data we have.html 154 Bytes
4. Distributions/6. Discrete Distributions and Their Characteristics..html 154 Bytes
4. Distributions/8. What is the Discrete Uniform Distribution.html 154 Bytes
[GigaCourse.com].url 49 Bytes

==查看完整文档列表==

上一个：3.The Traitor.mp357.6 MB
下一个：JUTA101 2.1 GB

种子标签

种子评价

优质的种子 (0) 假种子 (0) 有密码 (0) 低质量 (0) 有病毒 (0) 无法下载 (0)
欢迎对种子质量进行评价。

人气女优

北川ゆい Akira COCOLO Saiko あいだももあさのくるみあまいれもんいしかわ愛里いとうしいなうさみ恭香うちだまひろかぐやひめかとりこのみかないかほくすのき琴美クミコグレースくらもとまい（葉月ありさ）さとみ中村あみしいな純菜しのざきさとみ（三沢亜也）牧本千幸（つかもと友希）眞木ありさデヴィテラパトリックドミニカともさかまいともさか愛なごみもえひなこ

分享BT种子/磁力链接

亲，你知道吗？下载的人越多速度越快，赶快把本页面分享给好友一起下载吧^_^

2048BT

BT种子名称

[GigaCourse.com] Udemy - Probability for Statistics and Data Science

分享给好友

BT种子基本信息

下载磁力链接

下载BT种子

文档列表

猜你喜欢

种子标签

种子评价

最近搜索

人气女优

最新番号

分享BT种子/磁力链接

友情链接