Introduction the Robotic Operating System Robotic Operating System (ROS) is the development framework. It is the platform to write various algorithms to work with robots. Basically, any robotic process consists of sensing to collect the information from the outside environment and think accordingly with the info and then act accordingly. So, ROS plays an important …
Recommender systems The best example of the recommender system is “ amazon recommends us products based on other customer ratings ”. Basically, there are two types of recommender systems Content based recommendation Collaborative filtering recommender system. Collaborative filtering produces recommendations based on the knowledge of users’ attitude to items, that it uses the “wisdom of …
K Means Clustering This is an unsupervised machine learning algorithm ( which means it has no labeled data ). This will attempt to group similar clusters together. Let us consider few clustering examples Clustering similar documents Clustering customers based on features Market segmentation Identify similar physical groups Complete clustering process means dividing the data into …
Support Vector Machine This is a kind of supervised machine learning model of Support Vector Machine SVM with associated learning algorithms that analyzes the data and then predicts the data pattern. This model is used for classification and regression. It is given a set of few training examples, of two category classes. A SVM training …
Decision Trees and Random Forests In this tutorial we are building a machine learning model based on decision trees and random forest: First of all import the libraries import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns %matplotlib inline Next thing is to import our data as a …
Decision trees and random forests Topic covered in the last tutorials KNN Building a machine learning model using Knn Decision trees and random forests: This is a type of decision-making algorithm that builds a tree-like model. This model is not that efficient, it works well on trained data and not much effective for unknown data. …
KNN | model building In this tutorial, we would build our Knn machine learning model. We would be working with a dataset whose columns are not defined, they are just a few random things and we would select one column as our target variable. Then we would like to read our file : Now let …
k nearest neighbors In the previous tutorials, we have built a model using logistic regression that predicts the survival of a person in a titanic incident that happened long ago. In this tutorial, we will discuss the k nearest neighbors algorithm. KNN: K Nearest Neighbors is an algorithm that solves classification problems in a very …
Logistic Regression In this tutorial we will discuss briefly about the logistic regression and implement it. Building a classification model : Import the libraries and tools we will be using in logistic regression. Pandas – for data cleaning and processing Numpy – mathematical and logical operations Seaborn and matplot – for data visualization in graphical …
Logistic regression In the previous tutorials, we discussed linear regression and built a model to predict the values. In this tutorial we will get to know about Logistic Regression. Logistic regression: This regression is used to solve classification problems, It predicts discrete values. We cannot use linear regression to build a model on classification problems. …
