Python Machine Learning Code Snippets Collection
Python Machine Learning Code Snippets
Hierarchical Clustering Example
This snippet demonstrates hierarchical clustering using scipy and visualizes the result as a dendrogram, followed by applying Agglomerative Clustering.
import matplotlib.pyplot as plt
import scipy.cluster.hierarchy as sch
import numpy as np
from sklearn.cluster import AgglomerativeClustering
X = np.random.rand(50, 2)
dendrogram = sch.dendrogram(sch.linkage(X, method='ward'))
plt.title('Dendrogram')
plt.show()
hc = AgglomerativeClustering(Machine Learning Algorithms Implementation Showcase
# ============================
# 1. K-MEANS CLUSTERING
# ============================
# Create synthetic 2D data with 3 clusters
X_blobs, y_blobs = make_blobs(n_samples=300, centers=3, random_state=42)
# Fit KMeans
kmeans = KMeans(n_clusters=3, random_state=42, n_init=10)
kmeans.Fit(X_blobs)
# Get cluster labels
cluster_labels = kmeans.Labels_
centers = kmeans.Cluster_centers_
print(“KMeans cluster centers:\n”, centers)
# Plot clusters
plt.
Figure(figsize=(6, 5))
plt.Scatter(X_blobs[:, 0], X_blobs[:, 1], c=cluster_
CSMA/CD Ethernet Collision Detection and LAN Access
CSMA/CD Collision Detection in Ethernet LANs
CSMA/CD (Carrier Sense Multiple Access/Collision Detection) is a media access control method that was widely used in early Ethernet technology and LANs when networks used a shared bus topology and each node (computers) was connected by coaxial cables. Today, Ethernet is typically full-duplex and the topology is either star (connected via a switch or router) or point-to-point (direct connection). Hence, CSMA/CD is not commonly used in modern switched, full‑duplex
Read MoreMachine Learning Algorithms: KNN, LWR, Random Forest, SVM
K-Nearest Neighbors (KNN) Algorithm Implementation
This section demonstrates the implementation of the K-Nearest Neighbors (KNN) algorithm using the Iris dataset in Python with scikit-learn.
Python Code for KNN
from sklearn.datasets import load_iris
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import train_test_split
import numpy as np
# Load the Iris dataset
dataset = load_iris()
# Split the dataset into training and test sets
X_train, X_test, y_train, y_test =Deep Learning for Image Classification and Stock Prediction
Deep Learning Models for Image and Time Series Analysis
This document demonstrates the application of two prominent deep learning architectures: Convolutional Neural Networks (CNNs) for image classification and Long Short-Term Memory (LSTM) networks for time series forecasting. Each section provides a step-by-step implementation, from data preparation to model evaluation and prediction.
Convolutional Neural Networks for Image Classification
This section details the process of building and training
Read MoreNetworking Protocols: CSMA/CD, VTP, FTP, HDLC & More
Networking Protocols Explained
CSMA/CD (Carrier Sense Multiple Access with Collision Detection)
Carrier Sense Multiple Access with Collision Detection (CSMA/CD) is a network protocol for carrier transmission that operates in the Medium Access Control (MAC) layer. It senses or listens to whether the shared channel for transmission is busy or not, and defers transmissions until the channel is free. The collision detection technology detects collisions by sensing transmissions from other stations.