StatQuest 機器學習研習讀書會
StatQuest 機器學習研習讀書會是以StatQuest的機器學習課程為主，帶領學員每週一小時，從入門的機器學習概念開始，一步一步學習機器學習的奧秘，最後進入回歸、統計方法、神經網路，掌握大數據時
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Machine learning 基本觀念

12/2 回放【免費直播】StatQuest 機器學習讀書會  YouTube
💡 李宏毅/ StatQuest 研習讀書會時間：每週四的晚上 20:00 ~ 21:00。💡 直播平台：Youtube / Discord(https://discord.gg/VG45V6BC) 使用 Discord 可以獲得更好的互動體驗喔！💡 教材連結： 李宏毅讀書會：https:/...

12/02：A Gentle Introduction to Machine Learning
Machine Learning is one of those things that is chock full of hype and confusion terminology. In this StatQuest, we cut through all of that to get at the mos...

12/02：Cross Validation
One of the fundamental concepts in machine learning is Cross Validation. It's how we decide which machine learning method would be best for our dataset. Chec...

12/02：The Confusion Matrix
One of the fundamental concepts in machine learning is the Confusion Matrix. Combined with Cross Validation, it's how we decide which machine learning method...

12/02：Sensitivity and Specificity
In this StatQuest we talk about Sensitivity and Specificity  to key concepts for evaluating Machine Learning methods. These make it easier to choose which m...

12/02：ROC and AUC
ROC (Receiver Operator Characteristic) graphs and AUC (the area under the curve), are useful for consolidating the information from a ton of confusion matric...

12/02： Bias and Variance
Bias and Variance are two fundamental concepts for Machine Learning, and their intuition is just a little different from what you might have learned in your ...

12/16：The Main Ideas of Least Squares and Linear Regression
Fitting a line to data is actually pretty straightforward.⭐ NOTE: When I code, I use Kite, a free AIpowered coding assistant that will help you code faster ...

12/16：Linear Regression
The concepts behind linear regression, fitting a line to data with least squares and Rsquared, are pretty darn simple, so let's get down to it! NOTE: This S...

12/16：Using Linear Models for ttests and ANOVA
This StatQuest shows how the methods used to determine if a linear regression is statistically significant (covered in part 1) can be applied to ttests and ...

12/16：Design Matrices For Linear Models
In order to use general linear models (GLMs) you need to create design matrices. At first, these can seem intimidating, but this StatQuest puts together a bu...

12/30：StatQuest: Principal Component Analysis (PCA), StepbyStep  YouTube
Principal Component Analysis, is one of the most useful data analysis and machine learning methods out there. It can be used to identify patterns in highly c...

12/30：Neural Networks Pt. 3: ReLU In Action!!!  YouTube
The ReLU activation function is one of the most popular activation functions for Deep Learning and Convolutional Neural Networks. However, the function itsel...

12/30：Neural Networks Part 5: ArgMax and SoftMax  YouTube
When your Neural Network has more than one output, then it is very common to train with SoftMax and, once trained, swap SoftMax out for ArgMax. This video gi...

12/30：Regularization Part 1: Ridge (L2) Regression  YouTube
Ridge Regression is a neat little way to ensure you don't overfit your training data  essentially, you are desensitizing your model to the training data. It...

12/30：Regularization Part 2: Lasso (L1) Regression  YouTube
Lasso Regression is super similar to Ridge Regression, but there is one big, huge difference between the two. In this video, I start by talking about all of ...

12/30：Ridge vs Lasso Regression, Visualized!!!  YouTube
People often ask why Lasso Regression can make parameter values equal 0, but Ridge Regression can not. This StatQuest shows you why.NOTE: This StatQuest assu...


Statistics

pvalues: What they are and how to interpret them  YouTube
This StatQuest is all about interpreting pvalues. You've seen them online or in publications, or heard about them, whispered in dark, rave filled dance club...

Bootstrapping 拔靴法 (待刪除)

Bootstrapping 主要概念
Bootstrapping is one of the simplest, yet most powerful methods in all of statistics. It provides us an easy way to get a sense of what might happen if we co...

The Main Ideas behind Probability Distributions  YouTube
Here we demystify what a probability distribution is. It's not complicated, and we'll build on this in the coming weeks.⭐ NOTE: When I code, I use Kite, a fr...

The Normal Distribution, Clearly Explained!!!  YouTube
The normal, or Gaussian, distribution is the most common distribution in all of statistics. Here I explain the basics of how these distributions are created ...

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The normal, or Gaussian, distribution is the most common distribution in all of statistics. Here I explain the basics of how these distributions are created ...

The Central Limit Theorem, Clearly Explained!!!  YouTube
The Central Limit Theorem is a big deal, but it's easy to understand. Here I show you what it is, then I describe why this is useful and fundamental to Stati...

Population and Estimated Parameters, Clearly Explained!!!  YouTube
One of the most basic and most important thing we can do in statistics is estimate population parameters. This video explains what population parameters are ...

Calculating the Mean, Variance and Standard Deviation, Clearly Explained!!!  YouTube
One of the most basic things we do all the time in Data Analysis (i.e. Statistics, Machine Learning or any other sort of number crunching type thing) is calc...

Hypothesis Testing and The Null Hypothesis, Clearly Explained!!!  YouTube
One of the most basic concepts in statistics is hypothesis testing and something called The Null Hypothesis. This video breaks these concepts down into easy ...


Neural Network

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Entropy for data science
Entropy is a fundamental concept in Data Science because it shows up all over the place  from Decision Trees, to similarity metrics, to state of the art dim...

Cross Entropy
When a Neural Network is used for classification, we usually evaluate how well it fits the data with Cross Entropy. This StatQuest gives you and overview of ...

Cross Entropy Derivatives and Backpropagation
Here is a stepbystep guide that shows you how to take the derivative of the Cross Entropy function for Neural Networks and then shows you how to use that d...


Treebased Model
學習Gradient boost for Regression/classification 的概念和應用知識，還有較進階打比賽常用到的XGBoost方法。

StatQuest: Decision Trees
NOTE: This video has been updated and revised. The new version can be found here: https://youtu.be/_L39rN6gz7YThis StatQuest focuses on the machine learning ...

Gradient Boost Part 1 (of 4): Regression Main Ideas
Gradient Boost is one of the most popular Machine Learning algorithms in use. And get this, it's not that complicated! This video is the first part in a seri...

Gradient Boost Part 2 (of 4): Regression Details
Gradient Boost is one of the most popular Machine Learning algorithms in use. And get this, it's not that complicated! This video is the second part in a ser...

Gradient Boost Part 3 (of 4): Classification
This is Part 3 in our series on Gradient Boost. At long last, we are showing how it can be used for classification. This video gives focuses on the main idea...

Gradient Boost Part 4 (of 4): Classification Details
At last, part 4 in our series of videos on Gradient Boost. This time we dive deep into the details of how it is used for classification, going through algori...

Gradient Boost Part 3 (of 4): Classification (待刪除)
This is Part 3 in our series on Gradient Boost. At long last, we are showing how it can be used for classification. This video gives focuses on the main idea...
