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100_days_of_python

Welcome to my 100-day Python learning journey repository! 🎉 In this repository, I embark on a comprehensive 100-day exploration of Python programming, starting from the very basics and progressively advancing to more complex concepts. Each day of this journey, I commit to sharing my progress with you, providing detailed insights, explanations....

automobile-price-prediction

In this project, the task involves predicting car prices by training the model with a dataset containing various features and parameters of used cars. After experimenting with several algorithms, XGBoost (XGB) consistently exhibits the highest performance in price prediction across all metrics employed.

breast_cancer_prediction_using_artificial_neural_network_ann

In this Project we will be focusing on comparing the performance of machine learning techniques on predicting whether the cancer is Benign or Malignant according to a provided dataset involving breast cancer diagnosis.

employee-performance-analysis

In this IABAC project Analyze employee performance and predict ratings using machine learning. using classification approach with machine learning models such as Support Vector Classifier and Artificial Neural Network. project goal is providing accurate performance rating predictions and valuable insights into driving factors.

fifa-20

In this project, a predictive model has been developed to visualize FIFA 20 data. The exploration includes the application of unsupervised learning techniques, specifically Principal Component Analysis (PCA) for dimensionality reduction and clustering analysis.

hr_employee_attrition_using_support_vector_machine

In this Project the main goal is to predict whether an employee will leave the company or not.

khairnarrutuja

perceptron-algorithm

In this algorithm we used single perceptron and we get conclusion single layer perceptron is not work on non linear data

portuguese-bank-marketing

The Project is related to direct marketing campaigns of a Portuguese banking institution. The classification goal and task is to predict if the client will subscribe a term deposit (variable y).We used different type of model XGB and logistic model gives highest accuracy.

rice--leaf-disease-detection

In this project, implemented rice leaf disease detection using a deep learning model with a limited dataset. Employed extensive image augmentation techniques and a CNN model, with the primary goal being accurate disease recognition.

sales-effectiveness

In this project utilizes Machine Learning in FicZon Inc's lead management system to evaluate lead quality and enhance sales.By using Machine Learning, we want to predict which leads are really promising and which ones might not be as good for business.