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Dictionary in Python

Dictionary in Python

A dictionary is an example of a key-value store also known as Mapping in Python. It allows you to store and retrieve elements by referencing a key. As dictionaries are referenced by key, they have very fast lookups. As they…
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Voting Classifier

Voting Classifier in Machine Learning

Suppose you have trained a lot of classification models, and your each model is achieving the accuracy of 85 percent. A very simple way to create an even better classifier is to aggregate the predictions of each classifier and predict…
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Loops in Python

Loops in Python

As one of the most basic functions in programming, loops are an important piece to nearly every programming language. Loops enable developers to set certain portions of their code to repeat through several loops, referred to as iterations. This topic…
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Scraping Instagram

Scraping Instagram with Python

You must have seen many articles and tutorials on web scraping. Even I have written an article on it. In this article, I will do something different, that is scraping Instagram with Python. It is an easy task until you…
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Decision Boundary

Decision Boundary in Machine Learning

The general goal of a classification model is to find a decision boundary. The purpose of the decision boundaries is to identify those regions of the input class space that corresponds to each class. In this article, I will take…
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Data types in python

Data Types in Python

Data types are variables that are used to store values. In Python, variables do not need a pre declaration; the declaration of variables in Python happens automatically when we assign any value to a variable. Just like variables, data types…
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Anomaly Detection

Anomaly Detection with Machine Learning

Anomaly Detection means detecting unexpected events in the dataset which differ from the norm. Anomaly Detection is very often used in unlabeled data. There are two most important assumptions in the task of Anomaly Detection: the first assumption says that…
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Ridge Regression

Ridge Regression in Machine Learning

The Ridge Regression is a regularized version of a Linear Regression. The Ridge Regression enables the machine learning algorithms to not only fit the data but also to keep weights of the model as small as possible. It is quite…
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Machine Translation Model

Machine Translation Model

Machine Translation is one of the most challenging tasks in Artificial Intelligence that works by investigating the use of software to translate a text or speech from one language to another. In this article, I will take you through Machine…
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Audio Feature Extraction

Audio Feature Extraction

Audio Feature Extraction has been one of the significant focus of Machine Learning over the years. The most frequent common state of data is a text where we can perform feature extraction quite smoothly. Then we have Feature Extraction for…
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Polynomial Regression Algorithm

What will you do if your data is a bit more complicated than a straight line? A good alternative for you is that you can use a linear model to fit in a nonlinear data. You can use the add…
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Gradient Descent Algorithm in Machine Learning

Gradient Descent is an optimisation algorithm which is capable of providing optimal performance to a wide range of tasks in Machine Learning. The idea behind a Gradient Descent algorithm is to tweak the parameters using loops to minimize the cost…
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ROC Curve in Machine Learning

The Receiver Operating Characteristic (ROC) curve is a popular tool used with binary classifiers. It is very similar to the precision/recall curve. Still, instead of plotting precision versus recall, the ROC curve plots the true positive rate (another name for…
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Precision and Recall

In Machine Learning, Precision and Recall are the two most important metrics for Model Evaluation. Precision represents the percentage of the results of your model, which are relevant to your model. The recall represents the percentage total of total pertinent…
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Testing and Validation of a Model

Testing and Validation are the only way to know how well a model will generalize to new cases is to actually try it out on new cases. One way to do that is to put your model in production and…
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OpenAI Gym in Machine Learning

OpenAI Gym is a toolkit that provides a wide variety of simulated environments (Atari games, board games, 2D and 3D physical simulations, and so on), so you can train agents, compare them, or develop new Machine Learning algorithms (Reinforcement Learning).…
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Image Filtering with Machine Learning

Image filtering is used to enhance the edges in images and reduce the noisiness of an image. This technology is used in almost all smartphones. Although improving an image using the image filtering techniques can help in the process of…
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Data Visualization with Plotly

Data Visualisation plays a major role to study and analyse data to extract useful insights that can add value to our end task. Python being a universal language provides a lot of libraries for almost every task you have ever…
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Trading Strategy with Machine Learning

In this article I will take you through a Trading Strategy with Machine Learning, which can be used to determine when you should buy stocks and when you should sell. Generally it is not easy to predict stock market, but…
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