Machine Learning with Python-Principal Component Analysis with Python Principal Component Analyis is basically a statistical procedure to convert a set of observation of possibly correlated variables into a set of values of linearly uncorrelated variables. Each of the principal components is chosen in such a way so that it would describe most of the…
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Machine Learning with Python-Python | Decision Tree Regression using sklearn Decision Tree is a decision-making tool that uses a flowchart-like tree structure or is a model of decisions and all of their possible results, including outcomes, input costs and utility. Decision-tree algorithm falls under the category of supervised learning algorithms. It works for both…
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Machine Learning with Python-Python | Implementation of Movie Recommender System Recommender System is a system that seeks to predict or filter preferences according to the user’s choices. Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and products in general. Recommender systems produce a…
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Machine Learning with Python-Python | Image Classification using keras Image classification is a method to classify the images into their respective category classes using some method like : Training a small network from scratch Fine tuning the top layers of the model using VGG16 Let’s discuss how to train model from scratch and classify the…
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Machine Learning with Python-Multidimensional data analysis in Python Multi-dimensional data analysis is an informative analysis of data which takes many relationships into account. Let’s shed light on some basic techniques used for analysing multidimensional/multivariate data using open source libraries written in Python. Find the link for data used for illustration from here. Following code is…
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Machine Learning with Python-ML | Unsupervised Face Clustering Pipeline Live face-recognition is a problem that automated security division still face. With the advancements in Convolutions Neural Networks and specifically creative ways of Region-CNN, it’s already confirmed that with our current technologies, we can opt for supervised learning options such as FaceNet, YOLO for fast and…
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Machine Learning with Python-Analysis of test data using K-Means Clustering in Python This article demonstrates an illustration of K-means clustering on a sample random data using open-cv library. Pre-requisites: Numpy, OpenCV, matplot-lib Let’s first visualize test data with Multiple Features using matplot-lib tool. # importing required tools import numpy as np from matplotlib import pyplot…
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Machine Learning with Python-K means Clustering – Introduction We are given a data set of items, with certain features, and values for these features (like a vector). The task is to categorize those items into groups. To achieve this, we will use the kMeans algorithm; an unsupervised learning algorithm. Overview (It will help if you…
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Machine Learning with Python-Understanding Logistic Regression Pre-requisite: Linear Regression This article discusses the basics of Logistic Regression and its implementation in Python. Logistic regression is basically a supervised classification algorithm. In a classification problem, the target variable(or output), y, can take only discrete values for given set of features(or inputs), X. We can also say…
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Machine Learning with Python-Linear Regression Using Tensorflow Prerequisites We will briefly summarize Linear Regression before implementing it using Tensorflow. Since we will not get into the details of either Linear Regression or Tensorflow Brief Summary of Linear Regression Linear Regression is a very common statistical method that allows us to learn a function or relationship…
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