There are no reviews yet. Be the first to send feedback to the community and the maintainers!
Cotton-Disease-Prediction
Exploratory-Data-Analysis
Exploratory data analysis for deeper understanding of data Goal: Perform analysis on dataset of different cars with their specifications. • Before performing exploratory data analysis (EDA), data profiling was performed. • Dataset was checked up for missing values and treated with automate way to fill in the missing values using Imputer library. • After treatment of missing values, univariate, bivariate and multivariate charts and plots for deeper understanding of data.Regularization
Ridge & Lasso (Tuning Grid)NLP-Project-Classification-
Goal : The goal of the project is to identify such emails in the given day based on the above inappropriate content as classify them as Abusive and Non-abusive.Multiple-Linear-Regression.
Multiple-Linear-Regression
Machine LearningDecision-Tree-Classification
Classification Problem of Decision TreeRandom-Forest
ROC---AUC-Curve
Receiver Operating Characteristic - Area Under CurveWeb-Scraping-of-Flipkart
Web scraping is done on Mobile CategoriesNLP-Basic-Natural-Language-Processing-
Natural Language Processing (NLP) MODELS Present: 1.Tokenization 2.Stemming 3.Lemmatization 4.Bag of Words 5.TF-IDF (Term Frequency- Inverse Document Frequency) 6.Word2VecTime-Serirs-Forecasting-on-AirPassengers-Dataset
Goal: Forecasting number of passengers for airlines from 1949 to 1960 for every month. • Training has been done with AR(Auto-Regression model. Techniques like Rolling mean and Ad fuller were used to check the conversion into stationary time-series.Proect-3--Credit-Card-Limit-Analysis
Goal: To find factors affecting limit of credit card using Credit data set. Performed data profiling, data preprocessing and exploratory data analysis on the dataset. Used multiple linear regression performed regularization to increase accuracy. Compared accuracy of multiple linear regression with Decision tree regressor and KNN.K-Means-Cluster-on-Mall-Customers
Goal:Understand about customers coming up in mall. Performed steps of data profiling, data preprocessing and exploratory data analysis on the dataset. Used K-Means clustering and Hierarchical clustering for clusters formation.Loan-Approval-Prediction
Classification Problem as Loan Status of an employee is found using categorical variable (Y,N) STEPS PERFORMED: • Import Dataset • Data Profiling •Data Pre-processing •Exploratory Data Analysis •Split Data into training & testing set and create models(Compare Accuracy) •Compare predicted and achieved results MODELS USED: Logistic Regression Decision Tree Classification Random Forest K-Nearest NeighboursMotherboard-defect
Lane-Detection-using-Open-CV
Aim: To detect Road lanes line using Open-CVOne_Hot_Encoding
Includes Adj. R-squared, R-squared:Language-Translation
Bird-Species_Classification-Project
Handwritten-Digit-Project
LGMVIP-DataScience
LetsGrowMore Data Science InternLane-Detection-using-Mask-R-CNN
Aim: To detect the Road LAnes lines using Mask R-CNNMask-Detection-using-Yolov4
Aim: To detect if person wearing mask or not using Yolov4 Object detection model.AI_Coding_Test
Specialized in ML or DLEmployee-Retention-Dashboard
The Employee Retention Dashboard is been made on Tableau data visualization Tool. It gives the complete information about the Employee Retention datasets, based upon the features present in it. Using the important features we can prevent the retention, which will help the organizations growth.2D-image-to-3D-Model
The Goal of this project is to convert the 2-dimensional colour image into 3-dimensional model using the Open3d library. Depth Estimation is used to convert the 2-dimensional colour image to Point Clouds and then convert it into 3d Mesh using open3d.Love Open Source and this site? Check out how you can help us