ML - Aspires

ML

A collection of 7 posts

Code Analysis of Cycle-GAN

Code Analysis of Cycle-GAN

This is a code analysis of Cycle-GAN. The original code is here which is the implementation of the paper Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks.

Understanding Naïve Bayes Algorithm

Understanding Naïve Bayes Algorithm

Naïve Bayes is a classical machine learning algorithm. By reading this post, you will understand this algorithm and implement a Naïve Bayes classifier for classifying the target customer of an ad. by the features of the customer.

Terms Explanations in Deep Learning

Terms Explanations in Deep Learning

Binary Classification A classification method that yields a model $\hat{y} = wx+b$ for a specific x input and gets the corresponding predicted y (so called $\hat{y}$ ). Logistic Regression Transpose prediction $\hat{y}$ to a logical and explainable value to a Binary classification model. Transpose function like Sigmoid function:

Implementing Neural Networks from Scratch

Implementing Neural Networks from Scratch

In this post, we’ll understand how neural networks work while implementing one from scratch in Python.

Linux and Python AI Toolkits

Linux and Python AI Toolkits

This lecture contains two parts, namely Python fundamental and Machine Learning. Moreover, all of the process will be running on the Linux machine, which means that it will contain the part of knowledge in Linux shell. The content is structured, detailed in several chapters. Everyone is welcome to have a

Kaggle Titanic: Survive prediction

Kaggle Titanic: Survive prediction

This post is a recording of learning ML with Kaggle, For the competition, link click here. This is a 73.68% accurate model with Random Forest Classifier. Intro Let take a glance at the notebook, here we go! We need the following packages. import warnings warnings.filterwarnings('ignore') import numpy

Implementing Convolutional Neural Networks with Keras

Implementing Convolutional Neural Networks with Keras

Introduction Keras is a Deep Learning library for Python, after learning Intro to Neural Networks and Intro to Convolutional Neural Networks from Victor Zhou, These two posts produce implementations of Neural Networks and CNN from scratch (using only NumPy), To refresh the knowledge while reviewing it, I decided to write