By Jiayi

Deep Learning Basics 1

Logistic Regression with a Neural Network mindset

Welcome to your first (required) programming assignment! You will build a logistic regression classifier to recognize cats. This assignment will step you through how to do this with a Neural Netwo...

Posted by Jiayi on January 4, 2020

Clustering via 𝑘 -means

Clustering via 𝑘 means In many applications, the data have no labels but we wish to discover possible labels (or other hidden patterns or structures). This problem is one of unsupervised learning....

Posted by Jiayi on November 14, 2019

SVM

Support Vector Machine

1. SVM支持向量机： The princile of SVM is to find out hyper plan between two classes of datasets. What this line does that the other ones don’t do? It maximizes the distance to the nearest point, and ...

Posted by     Jiayi on March 20, 2018

What is Blockchain

Is Blockchain application just around the corner?

Although the Internet has connected the world closer, it is accompanied with growing gap of trust. Looking at the current business environment, trust is probably the most we lack. Trust is actually...

Posted by Jiayi on February 4, 2018

Linear Regression

Loss Function & Gradient Descent

Linear regression is a method used to find a relationship between a dependent variable and a set of independent variables. In its simplest form it consist of fitting a function $ \boldsymbol{y} = w...

Posted by     Jiayi on December 16, 2017

Introduction to Deep Learning

01 Basics

01 Basics Forward propagation import numpy as np input_data = np.array([2,3]) weights = {'node_0': np.array([1,1]), 'node_1': np.array([-1,1]), 'output': np.array([2,-1])}...

Posted by     Jiayi on October 3, 2017

Understanding decision trees

Part I

Recursive partitioning:also known as divide and conquer because it splits the data into subsets, which are then split repeatedly into even smaller subsets, and so on and so forth until the process ...

Posted by     Jiayi on August 11, 2017

Basic concepts of Bayesian methods

A study note from 'Machine Learning with R, 2nd edition'

What is Naive Bayes? Naive Bayes assumes class-conditional independence, which means that events are independent so long as they are conditioned on the same class value. The probability of both ha...

Posted by     Jiayi on July 28, 2017

Lazy Learning - Classification Using Nearest Neighbors

A study note from 'Machine Learning with R, 2nd edition'

Understanding classification using nearest neighbors Define feature, link your train example (food) to the result (food type) Treat the features as coordinates in a multidimensional feature s...

Posted by Jiayi on July 27, 2017

Titanic Machine Learning from Disaster

Start here! Predict survival on the Titanic and get familiar with ML basics

Preface: This is the competition of Titanic Machine Learning from Kaggle The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voy...

Posted by Jiayi on June 15, 2017

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