| 00001 Introduction.mp4 | 94.9 MB | ||
| 00002 Code_Environment_Setup_and_Python_Crash_Course.mp4 | 321 MB | ||
| 00003 Getting_Started_with_Code_-_Feel_of_Data.mp4 | 213.9 MB | ||
| 00004 Foundations_Data_Types_and_Representing_Data.mp4 | 371.1 MB | ||
| 00005 Practical_Note_-_One-Hot_Vector_Encoding.mp4 | 84.1 MB | ||
| 00006 Exploring_Data_Types_in_Code.mp4 | 231.1 MB | ||
| 00007 Central_Tendency_Mean_Median_and_Mode.mp4 | 858.5 MB | ||
| 00008 Dispersion_and_Spread_in_Data_Variance_Standard_Deviation.mp4 | 92.6 MB | ||
| 00009 Dispersion_Exploration_Through_Code.mp4 | 196.6 MB | ||
| 00010 Introduction_to_Uncertainty_Probability_Intuition.mp4 | 135.1 MB | ||
| 00011 Simulating_Coin_Flips_for_Probability.mp4 | 300.8 MB | ||
| 00012 Conditional_Probability_the_Most_Important_Concept_in_Stats.mp4 | 290.7 MB | ||
| 00013 Applying_Conditional_Probability_-_Bayes_Rule.mp4 | 136.8 MB | ||
| 00014 Application_of_Bayes_Rule_in_the_Real_World_-_Spam_Detection.mp4 | 138.4 MB | ||
| 00015 Spam_Detection_-_Implementation_Issues.mp4 | 723.7 MB | ||
| 00016 Rules_for_Counting_Mostly_Optional.mp4 | 195.9 MB | ||
| 00017 Quantifying_Events_-_Random_Variables.mp4 | 111.3 MB | ||
| 00018 Two_Random_Variables_-_Joint_Probabilities.mp4 | 188.9 MB | ||
| 00019 Distributions_-_Rationale_and_Importance.mp4 | 252.1 MB | ||
| 00020 Discrete_Distributions_Through_Code.mp4 | 77.4 MB | ||
| 00021 Continuous_Distributions_with_the_Help_of_an_Example.mp4 | 193.2 MB | ||
| 00022 Continuous_Distributions_Code.mp4 | 78.6 MB | ||
| 00023 Case_Study_-_Sleep_Analysis_Structure_and_Code.mp4 | 1 GB | ||
| 00024 Visualizing_Joint_Distributions_-_The_Road_to_ML_Success.mp4 | 206.3 MB | ||
| 00025 Dependence_and_Variance_of_Two_Random_Variables.mp4 | 190.5 MB | ||
| 00026 Expected_Values_-_Decision_Making_Through_Probabilities.mp4 | 63.3 MB | ||
| 00027 Entropy_-_The_Most_Important_Application_of_Expected_Values.mp4 | 242 MB | ||
| 00028 Applying_Entropy_-_Coding_Decision_Trees_for_Machine_Learning.mp4 | 547.5 MB | ||
| 00029 Foundations_of_Bayesian_Inference.mp4 | 106.7 MB | ||
| 00030 Bayesian_Inference_Code_Through_PyMC3.mp4 | 314.8 MB | ||
| Probability-Statistics---The-Foundations-of-Machine-Learning-main.zip | 55.2 MB | ||
| [CourseClub.Me].url | 102.4 B | ||
| [GigaCourse.Com].url | 0 B | ||
| ▲ 35 total files | |||
[PacktPub] Probability / Statistics – The Foundations Of Machine Learning [Video]
The objective of this course is to give you a solid foundation needed to excel in all areas of computer science—specifically data science and machine learning. The issue is that most of the probability and statistics courses are too theory-oriented.
Author(s): Dr. Mohammad Nauman
Language: English
Released: June 2022
Videos Duration: 6h 34m
TO GET DIRECT DOWNLOAD LINKS OR GOOGLE DRIVE LINKS VISIT OUR WEBSITE
FOR MORE UDEMY AND OTHER COURSES VISIT: https://gigacourse.com
FOR MORE OTHER COURSES VISIT: https://Courseclub.me
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
|
PacktPub | Probability / Statistics - The Foundations Of Machine Learning [FCO] Posted by
Prom3th3uS in Other
|
7.89 GB | Prom3th3uS | 3 years | 1 | 0 |
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