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Mohd Shazan
@MohdShazan
Tauqeer Sayeed
@TauqeerSayeed
Mohammad Naif
@NAIF4601
Owais Ahmad
@Owaiskhan9654
Karimkhan
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Objective of this project is to build an accurate and efficient computer vision model capable of detecting industrial equipment in images.
Task is to build a model that predicts the total ride duration of taxi trips in New York City. primary dataset is one released by the NYC Taxi and Limousine Commission, which includes pickup time, geo-coordinates, number of passengers, and many other variables
What is K-fold in cross-validation? K-fold Cross-Validation is when the dataset is split into a K number of folds and is used to evaluate the model's ability when given new data. K refers to the number of groups the data sample is split into. For example, if you see that the k-value is 5, we can call this a 5-fold cross-validation.
What is gradient boosting regression in machine learning? Image result for gradient boosting algorithm Gradient boosting Regression calculates the difference between the current prediction and the known correct target value. This difference is called residual. After that Gradient boosting Regression trains a weak model that maps features to that residual.
we are going to see the Olympics analysis using Python. The modern Olympic Games or Olympics are leading international sports events featuring summer and winter sports competitions in which thousands of athletes from around the world participate in a variety of competitions. The Olympic Games are considered the world’s foremost sports competition with more than 200 nations participating. The total number of events in the Olympics is 339 in 33 sports. And for every event there are winners. Therefore various data is generated. So, by using Python we will analyze this data. Modules Used Pandas: It is used for analyzing the data, NumPy: NumPy is a general-purpose array-processing package. Matplotlib: It is a numerical mathematics extension NumPy seaborn: It is used for visualization statistical graphics plotting in Python
Topic modeling is a machine learning technique that automatically analyzes text data to determine cluster words for a set of documents. This is known as 'unsupervised' machine learning because it doesn't require a predefined list of tags or training data that's been previously classified by humans
What is meant by hierarchical clustering? Image result for hierarchical clustering Hierarchical clustering is a popular method for grouping objects. It creates groups so that objects within a group are similar to each other and different from objects in other groups. Clusters are visually represented in a hierarchical tree called a dendrogram.
SVM or Support Vector Machine is a linear model for classification and regression problems. It can solve linear and non-linear problems and work well for many practical problems. The idea of SVM is simple: The algorithm creates a line or a hyperplane which separates the data into classes.
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