一些常用的机器学习算法实现
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Updated
Apr 19, 2018 - Python
一些常用的机器学习算法实现
This repository contains all the Lab and Assignments from Andrew NG Machine Learning Specialization Course on Coursera.
Data Mining Algorithms with C# using LINQ
𝗙𝗶𝗿𝗲 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻🔥using Machine Learning Algorithm with python🐍, GoogleColab & database taken from 𝗨𝗖𝗜 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆
Leveraging the power of Machine Learning as a tool, we delve into the realm of app permissions to discern the true nature of applications, whether they harbor malicious or benign intent. By analyzing and predicting based on these permissions, we unlock valuable insights to safeguard users in the digital landscape.
A Collection of Most Famous Machine Learning Models Implementation
Explore ML mini-projects with Jupyter notebooks. Discover predictive analysis for commercial sales, leveraging regression models such as linear regression, decision trees, random forests, lasso, ridge, and extra-trees regressor.
Nations Flags Classification & Clustering project. 🎏
This code build up a predicting model use the Machine learning algorithms such as Decision Tree, k-Nearest Neighbors etc. on the Vehicle to predict the departure action
Efficient Android Malware detection using Random - Protype of BA's final project (Efficient Android Malware Detection using RL) - Amit Moshe (@Amit223) & Inbar Roth (@Inbaroth) & Liad Bercovich (@liadber)
Diabetes prediction using PIMA Indians dataset
Show several visualizations in the form query, histograms, bar charts and pie charts and others. In this analysis approach, the target variable is limited or categorical, in the form of YES or NO (binary). Based on this, I will analyze the income group with seven methods Supervised Learning.
Text Classification that works on identifying different authors writing styles in Gutenberg Digital Books | NLP.
Collect sensor data from Android cell phone.Using accelerometers and gravimeters to calculate horizontal and vertical accelerations. Use decision tree as classifier
Uji coba model menggunakan 3 algorima machine learning untuk klasifikasi
Decision Support System Application with Machine Learning Approach in Diagnosis of Diabetes
This ML project predicts cardiovascular diseases using clinical data (blood pressure, cholesterol, heart rate). Implemented Decision Tree (71.15%) and Gaussian Naive Bayes (70.49%) models on 13 medical features.
These are all of my machine learning codes.You can find every code about machine learning.
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