XLSOR’s Post

🍊 Just completed a project using machine learning to predict orange quality! Applied Random Forest, KNN, XGBoost, and Decision Trees, achieving enhanced accuracy in fruit grading. #DataScience #MachineLearning #DataAnalytics

Decision Tree Classifier is a supervised machine learning algorithm which is used in classification to classify the dataset. In this task a Decision Tree Classifier is used to classify the types of flowers. #MachineLearning #GRIPMAY24 #DataScience The Sparks Foundation

Data Set Information: Images of Kecimen and Besni raisin varieties grown in Turkey were obtained with CVS. A total of 900 raisin grains were used, including 450 pieces from both varieties. These images were subjected to various stages of pre-processing and 7 morphological features were extracted. These features have been classified using three different artificial intelligence techniques. https://lnkd.in/daQJCcJB

Understanding the run time of #ML algorithms is important because it helps us: - Build a core understanding of an algorithm. - Understand the data-specific conditions that allow us to use an algorithm. For instance, using SVM or t-SNE on large datasets is infeasible because of their polynomial relation with data size. Similarly, using OLS on a high-dimensional dataset makes no sense because its run-time grows cubically with total features.

Cat Boost: A High-Performance Gradient Boosting Library ▸ https://lttr.ai/AKjRA #BlogPostExplores #PreventOverfitting #·11MinRead·Just #StrongOnlineCommunity #DecisionTreeAlgorithms #AvoidingCommonMistakes #PowerfulToolEmerged #EnsuringAccuratePredictions #DataMeetsAlgorithms #MachineLearningAlgorithms

K-Means is an important tool to deal with the classification problem. It is an supervised machine learning algorithm which can make the clusters of your datasets on the basis of similarities between the data. The number of cluster for best prediction of your dataset is got by finding the elbow point. In this task I have trained a model using the k-means technique which can predict the type of flower on the basis of its input features. #GRIPMAY24 #MachineLearning #DataScience The Sparks Foundation

I'm thrilled to share my completion of Task 1 for Prodigyinfotech, where I applied linear regression to crack the code of house price prediction! Watch my video to see how I tackled this challenge and stay tuned for more updates from my machine learning journey! #Prodigyinfotech #HousePricePrediction #LinearRegression #MachineLearning #DataScience

https://lnkd.in/duaKtXWn Face replacement of Bejby Blue using custom developed Machine Learning pipeline

Happy to share our latest published paper entitled 'Integrating APSIM model with machine learning to predict wheat yield spatial distribution'

Task 3 Classified Iris flowers by species using machine learning! 🌺 Leveraged the classic Iris dataset to train a model that can distinguish between Iris setosa, versicolor, and virginica based on sepal and petal measurements. Explored data preprocessing, feature selection, and several classification algorithms to build an accurate flower identification system. A great intro to supervised learning! #DataScience #MachineLearning #FlowerClassification #Codsoft