Gradient Boosting
One of the most appreciated is the Gradient Boosting Machine. The gradient boosting algorithm or GBM can be explained in relation to the AdaBoost Algorithm.Boosting is explained as a manner of...
View ArticleIntroduction to Neuroevolution
Neuroevolution is a strategy for altering neural system loads, topologies, or gatherings to become familiar with a particular errand.Transformative calculation (see Evolutionary Algorithms) is utilized...
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Support Vector Machine
Support Vector Machine (SVM) is a powerful algorithm developed by Vladimir Vapnik and Alexey Chervonenkis in 1963. Although its roots date back to the 60s, its popularity in the machine learning...
View ArticleExtract text from image
Extracting text from images is an essential task in the realm of machine learning. One of the prominent methods to achieve this is through Optical Character Recognition (OCR). This technique has gained...
View ArticleSpeech Recognition in Python (Text to speech)
We can make the computer speak with Python. Given a text string, it will speak the written words in the English language.This process is called Text To Speech (TTS).Related Course:The Complete Machine...
View ArticleSpeech Recognition examples with Python
Speech recognition technologies have experienced immense advancements, allowing users to convert spoken language into textual data effortlessly. Python, a versatile programming language, boasts an...
View ArticleLanguage Translation in Python
We can use a language translator to translate text from one language to another.There are various APIs and modules for this, we’ll use the Google Translate API.We will use the Goslate module to...
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logistic regression spam filter
Lets make a spam filter using logistic regression. We will classify messages to be either ham or spam. The dataset we’ll use is the SMSSpamCollection dataset. The dataset contains messages, which are...
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Linear Regression
We can help understand data by building mathematical models, this is key to machine learning.One of such models is linear regression, in which we fit a line to (x,y) data. There are many modules for...
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kmeans text clustering
Given text documents, we can group them automatically: text clustering. We’ll use KMeans which is an unsupervised machine learning algorithm.I’ve collected some articles about cats and google. You’ve...
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kmeans elbow method
Find k for kmeans using the elbow method?The KMeans algorithm can cluster observed data. But how many clusters (k) are there?The elbow method finds the optimal value for k (#clusters).Related...
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kmeans clustering centroid
The KMeans clustering algorithm can be used to cluster observed data automatically. All of its centroids are stored in the attribute cluster_centers. In this article we’ll show you how to plot the...
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k-nearest neighbor algorithm versus k-means clustering
Data science is considered to be one of the most exciting fields in which you could work due to the fact that it combines both advanced statistical and quantitative skills with real-world programming...
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kmeans clustering algorithm
Do you have observed data?You can cluster it automatically with the kmeans algorithm.In the kmeans algorithm, k is the number of clusters.Clustering is an _unsupervised machine learning task. _...
View Articlek Nearest Neighbors
The k-nearest neighbors or simply KNN algorithm represents an easy-to-use supervised machine learning tool that can aid you in solving both classification and regression problems.So, what does actually...
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Decision tree visual example
A decision tree can be visualized. A decision tree is one of the many Machine Learning algorithms.It’s used as classifier: given input data, it is class A or class B? In this lecture we will visualize...
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Decision trees in Python with Scikit-Learn
Decision Trees: An Intuitive Approach with Scikit-Learn in PythonDecision trees are powerful and intuitive machine learning algorithms that mimic a tree-like decision-making process. This methodology...
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Advantages of a Decision Tree for Classification
Decision tree is one of the simplest and most popular classification algorthms to learn, understand, and interpret. In is often utilized to deal with classification and regression problems.Related...
View Articlebag of words euclidian distance
The bag-of-words model is a model used in natural language processing (NLP) and information retrieval. It converts a text to set of words with their frequences, hence the name “bag of words”. If we...
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Bag of Words Algorithm in Python Introduction
If we want to use text in Machine Learning algorithms, we’ll have to convert then to a numerical representation. It should be no surprise that computers are very well at handling numbers.We convert...
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