Glass dataset kaggleFeb 04, 2020 · An example use case for DeLong’s test: Model A predicts heart disease risk with AUC of 0.92, and Model B predicts heart disease risk with AUC of 0.87, and we use DeLong’s test to demonstrate that Model A has a significantly different AUC from Model B with p < 0.05. Elizabeth Ray DeLong is a statistician and professor at Duke University. Dataset Information. The original Ecoli dataset from UCI machine learning repository is a multiclass classification dataset having 8 attributes. Here, 7 numerical attributes are utilized and the attribute "sequence name" is omitted. Among the 8 classes omL, imL, and imS are the minority classes and used as outliers.Jul 15, 2019 · Methods. The demo dataset contains data associated with (ICU) stays for over 2,500 unit stays selected from 20 of the larger hospitals in the eICU Collaborative Research Database. All tables are deidentified to meet the safe harbor provision of the US Health Insurance Portability and Accountability Act (HIPAA). Feb 04, 2020 · An example use case for DeLong’s test: Model A predicts heart disease risk with AUC of 0.92, and Model B predicts heart disease risk with AUC of 0.87, and we use DeLong’s test to demonstrate that Model A has a significantly different AUC from Model B with p < 0.05. Elizabeth Ray DeLong is a statistician and professor at Duke University. Sep 24, 2020 · using a dataset that has multiple numeric columns in which the values are on different scales. You want to transform the numeric columns so that the values are all on a similar scale based relative to the minimum and maximum values in each column. Which module should you add to the pipeline? 1: Select Columns in a Dataset 2: Normalize Data Request PDF | Archaeology and the silk road model | In modern scholarship, the 'Silk Road' is used as a broad framework for networked exchanges across ancient Eurasia, periodized roughly ...README.md kaggle-glass-classification-nn-model An analysis of kaggle glass dataset as well as building a neural network. In this work Neural Network is built with considering optimized parameters using hyperopt and hyperas libraries. I made use of oversampling and undersampling tools from imblearn library like SMOTE and NearMiss .Open dataset featuring non-invasive electrophysiological recordings, fetal pulsed-wave Doppler and maternal respiration signals. It provides a ground truth on the fetal heart activity when an invasive scalp lead is unavailable.Jan 05, 2021 · Each dataset will be loaded and the nature of the class imbalance will be summarized. Glass Identification (Glass) Each record describes the chemical content of glass and prediction involves the type of glass. More Details: glass.names; Dataset: glass.csv; Additional Information; Below provides a sample of the first five rows of the dataset. A machine a learning framework was employed to predict COVID-19 from Chest X-ray images. Unlike the classical approaches for medical image classification which follow a two-step procedure (hand-crafted feature extraction+recognition), we use an end-to-end deep learning framework which directly predicts the COVID-19 disease from raw images without any need of feature extraction.Data Set Information: Vina conducted a comparison test of her rule-based system, BEAGLE, the nearest-neighbor algorithm, and discriminant analysis. BEAGLE is a product available through VRS Consulting, Inc.; 4676 Admiralty Way, Suite 206; Marina Del Ray, CA 90292 (213) 827-7890 and FAX: -3189. In determining whether the glass was a type of ...Exploring Dataset Preparing Dataset Cleaning (removing outliers, normalizing) Visualization Train/Test Split Applying Machine Learning Models Summary Method 2 to solve dataset (Different method to detect glasses) Machine Learning Models that we have applied: KNN Logistic Regression Decision Tree SVM (Linear Kernal) SVM (Non Linear Kernal)See how organizations have used the BigQuery COVID-19 public dataset for research, healthcare, and more. These datasets remove barriers and provide access to critical information quickly and easily, eliminating the need to search for and onboard large data files. Researchers can access the datasets from within the Google Cloud Console, along ...For this purpose we are using the iris flower dataset which is available in the kaggle webiste. Lets plot the density plot for sepal length and with varibales. Execute the below code to create a 2D density plot in R studio. Request PDF | Archaeology and the silk road model | In modern scholarship, the 'Silk Road' is used as a broad framework for networked exchanges across ancient Eurasia, periodized roughly ...Exploratory Data Analysis - Glass Classification Dataset. Day 6 of 100 Days of Exploratory Data Analysis. Content. This is a Glass Identification Data Set from UCI.Dec 04, 2021 · K-fold cross validation is a data splitting technique that can be implemented with k > 1 folds. K-Fold Cross Validation is also known as k-cross, k-fold cross validation, k-fold CV and k-folds. The k-fold cross validation technique can be implemented easily using Python with scikit learn package which provides an easy way to calculate k-fold ... Sep 24, 2020 · using a dataset that has multiple numeric columns in which the values are on different scales. You want to transform the numeric columns so that the values are all on a similar scale based relative to the minimum and maximum values in each column. Which module should you add to the pipeline? 1: Select Columns in a Dataset 2: Normalize Data I think UCI has many multi class datasets as example wine, glass, seeds, sat images. You can also see Keels dataset repository and in fact the kaggle datasets are also very contemporary you can...An ambiguous something in yaml file. Bookmark this question. Show activity on this post. I am a beginner at computer vision and I'm trying to build a model that can recognizes Egyptian currency. My dataset folder is structured as followed: Data -> train -> images,labels. This is the yaml file I want to modify. Train and validation paths must be ...Sample Weka Data Sets Below are some sample WEKA data sets, in arff format. contact-lens.arff; cpu.arff; cpu.with-vendor.arff; diabetes.arff; glass.arffExplore and run machine learning code with Kaggle Notebooks | Using data from ECG Heartbeat Categorization Dataset DA: 96 PA: 28 MOZ Rank: 61 GitHub - YuzheYang/ECG-Heartbeat-Categorization …When I try to deal with a large dataset with lots of features, I get stuck with it. ... For example, this one about house price prediction on Kaggle: ... Glass Identification by USA Forensic Science Service. Identify the Type of animal (7 Types) based on the available attributes.Kaggle . README.md . View code README.md. Diaglass_Dataset. Dia-Glass: A Calorie Management System for Diabetic Patients using Augmented Reality andFaster R-CNN. About. Dia-Glass: A Calorie Management System forDiabetic Patients using Augmented Reality andFaster R-CNN Resources.ground-glass, consolidation, and pleural effusion. As a result, a data set that contains 100 axial CT slices from 60. ... a data set from Kaggle. 12, and a data set of common.Mar 11, 2022 · X-ray Kaggle CXR collection, which is composed of 5863 CXRs. 1583 is normal and the remaining shows manifestations of viral and Bacterial Pneumonia. Consists of Shenzhen, China regions (340 normal + 342 tuberculosis) and Montgomery County, USA region (80 normal + 58 Tuberculosis) dataset. In categorising COVID- In particular, we focus on learning to segment left lung, right lung, and infections using pure but limited COVID-19 CT scans; existing labeled lung CT dataset from other non-COVID-19 lung diseases; heterogeneous datasets include both COVID-19 and non-COVID-19 CT scans.Investigate a dataset on wine quality using Python November 12, 2019 1 Data Analysis on Wine Quality Data Set Investigate the dataset on physicochemical properties and quality ratings of red and white wine samples. 1.0.1 Gathering Data [103]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns ...Feb 20, 2022 · The data sets are usually found in Our CSV classifier is going to take several arguments Deprecated The dataset is divided into five training batches and one test batch, each containing 10,000 images • It is a multi-purpose statistical package to help you explore, summarize and analyze datasets M7 • It is a multi-purpose statistical package ... Jul 15, 2017 · We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. Explore and run machine learning code with Kaggle Notebooks | Using data from Glass Classification Jul 15, 2017 · We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. Apr 26, 2020 · Dataset. COVID-19 images are gathered from several sources, primarily the covid-chest xray-dataset.The non-COVID pneumonia images are taken from the training images in the RSNA Pneumonia Detection Challenge on Kaggle. Most of the Chest Radiograph Images (CXR) are available in the Poster anterior views (PA). May 09, 2021 · The dataset is divided into 5 sets, 4 sets were used for the training and remaining is used for the testing. This process is carried out for all the sets and results are recorded. The average is calculated to evaluate the performance of the model. Further, the Kaggle-2 dataset is used to validate the proposed model. This paper presents widely used, avail-. able, open and free E EG datasets available for epilepsy. and seizure diagnos is. A brief compariso n and discus-. sion of open and priv ate datasets has ...Open dataset featuring non-invasive electrophysiological recordings, fetal pulsed-wave Doppler and maternal respiration signals. It provides a ground truth on the fetal heart activity when an invasive scalp lead is unavailable.Oct 20, 2019 · kaggle-glass-classification-nn-model An analysis of kaggle glass dataset as well as building a neural network. In this work Neural Network is built with considering optimized parameters using hyperopt and hyperas libraries. I made use of oversampling and undersampling tools from imblearn library like SMOTE and NearMiss . Explore and run machine learning code with Kaggle Notebooks | Using data from Glass Classification Kaggle . README.md . View code README.md. Diaglass_Dataset. Dia-Glass: A Calorie Management System for Diabetic Patients using Augmented Reality andFaster R-CNN. About. Dia-Glass: A Calorie Management System forDiabetic Patients using Augmented Reality andFaster R-CNN Resources.See full list on kaggle.com The dataset describes the chemical properties of glass and involves classifying samples of glass using their chemical properties as one of six classes. The dataset was credited to Vina Spiehler in 1987. Ignoring the sample identification number, there are nine input variables that summarize the properties of the glass dataset; they are:Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Flexible Data Ingestion.This dataset, available from the Trustfoto website, will be for those who work on the photographic images (PIM) versus photorealistic computer graphics (PRCG) classification problem, which is a subproblem of the passive-blind image authentication research. In technical report below, we describe the design and the implementation of the dataset.Introduction. This tutorial is an introduction to using Scikit-learn for machine learning in Python, focused on building a classifier to separate poisonous from edible mushrooms and to separate different types of glass.Scikit-learn is an excellent library for this purpose. Besides the fact that it does a lot of useful things for you right out of the box, saving you coding time, it's also ...Glass Multi-Class Classification Dataset. In this tutorial, we will focus on the standard imbalanced multi-class classification problem referred to as "Glass Identification" or simply "glass." The dataset describes the chemical properties of glass and involves classifying samples of glass using their chemical properties as one of six ...The dataset describes the chemical properties of glass and involves classifying samples of glass using their chemical properties as one of six classes. The dataset was credited to Vina Spiehler in 1987. Ignoring the sample identification number, there are nine input variables that summarize the properties of the glass dataset; they are:Kaggle offers a free tool for data science teachers to run academic machine learning competitions. Kaggle also hosts recruiting competitions in which data scientists compete for a chance to interview at leading data science companies like Facebook, Winton Capital, and Walmart . Impact of Kaggle competitionsMar 17, 2022 · An illustration of a magnifying glass. An illustration of a horizontal line over an up pointing arrow. Upload. An illustration of a person's head and chest. ... Al: Aluminum. Si: Silicon. K: Potassium. Ca: Calcium. Ba: Barium. Fe: Iron. Type of glass: (class attribute) -- 1 building windows float processed -- 2 building windows non float processed -- 3 vehicle windows float processed. -- 4 vehicle windows non float processed (none in this database)This paper presents widely used, avail-. able, open and free E EG datasets available for epilepsy. and seizure diagnos is. A brief compariso n and discus-. sion of open and priv ate datasets has ...Kaggle . README.md . View code README.md. Diaglass_Dataset. Dia-Glass: A Calorie Management System for Diabetic Patients using Augmented Reality andFaster R-CNN. About. Dia-Glass: A Calorie Management System forDiabetic Patients using Augmented Reality andFaster R-CNN Resources.Glass Multi-Class Classification Dataset. In this tutorial, we will focus on the standard imbalanced multi-class classification problem referred to as "Glass Identification" or simply "glass." The dataset describes the chemical properties of glass and involves classifying samples of glass using their chemical properties as one of six ...Take home coding test with a dataset from Kaggle. Analyze and visualize to give your key insights about dataset. You have to finish it within a week. It is not much difficult but the dataset is a liltle bit complicated so you might take time to cleaning before explore it. I am still waiting for the response from recruiter. Introduction. This tutorial is an introduction to using Scikit-learn for machine learning in Python, focused on building a classifier to separate poisonous from edible mushrooms and to separate different types of glass.Scikit-learn is an excellent library for this purpose. Besides the fact that it does a lot of useful things for you right out of the box, saving you coding time, it's also ...Data Set Information: Vina conducted a comparison test of her rule-based system, BEAGLE, the nearest-neighbor algorithm, and discriminant analysis. BEAGLE is a product available through VRS Consulting, Inc.; 4676 Admiralty Way, Suite 206; Marina Del Ray, CA 90292 (213) 827-7890 and FAX: -3189. In determining whether the glass was a type of ...Jul 21, 2020 · Here is the code which can be used for creating visualization. It uses the instance of decision tree classifier, clf_tree, which is fit in the above code. Note some of the following in the code: export_graphviz function of Sklearn.tree is used to create the dot file. Function, graph_from_dot_data is used to convert the dot file into image file. 1. COVID-19 image data collection ( 🎬 video about the project) Project Summary: To build a public open dataset of chest X-ray and CT images of patients which are positive or suspected of COVID-19 or other viral and bacterial pneumonias ( MERS, SARS, and ARDS .). Data will be collected from public sources as well as through indirect collection ... Investigate a dataset on wine quality using Python November 12, 2019 1 Data Analysis on Wine Quality Data Set Investigate the dataset on physicochemical properties and quality ratings of red and white wine samples. 1.0.1 Gathering Data [103]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns ...An imbalanced classification problem is a problem that involves predicting a class label where the distribution of class labels in the training dataset is skewed. Many real-world classification problems have an imbalanced class distribution, therefore it is important for machine learning practitioners to get familiar with working with these types of problems.The dataset features over 1,000 images across 10 separate categories including altar, column, dome (inner), dome (outer), stained glass, vault, flying buttress, apse, and bell tower. Fruits 360 - This dataset features 90,483 images of different fruits and vegetables. The training set features 67,692 images (one fruit or vegetable per image ...README.md kaggle-glass-classification-nn-model An analysis of kaggle glass dataset as well as building a neural network. In this work Neural Network is built with considering optimized parameters using hyperopt and hyperas libraries. I made use of oversampling and undersampling tools from imblearn library like SMOTE and NearMiss .In addition to NIST 610, three standards manufactured by Corning were employed. Glass standards B, C, and D are comparable to compositions of ancient glasses (Brill, 1999), where glass B is similar in composition to a soda-lime glass, glass C is a lead glass, and glass D is similar in composition to a potash-lime glass. 2.4. NAA analysisInvestigate a dataset on wine quality using Python November 12, 2019 1 Data Analysis on Wine Quality Data Set Investigate the dataset on physicochemical properties and quality ratings of red and white wine samples. 1.0.1 Gathering Data [103]: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns ...Aug 27, 2017 · For this exercise, I downloaded the Global Temperatures data from Kaggle rather than the one split by country because this data set contained various Land and Ocean temperatures split by date. I subsetted the column ‘LandAndOceanAverageTemperature’ – this was the list of vectors I wanted to try out the package with. Dataset split. As the dataset is intended to be used to train and evaluate machine learning-based image segmentation methods, we created a dataset split into training set and test set.The patients in this dataset are all females of at least 21 years of age from Pima Indian Heritage. It has 768 instances and 8 numerical attributes plus a class. This is a binary classification dataset where the output variable predicted is nominal comprising of two classes. ionosphere.arff. This is a popular dataset for binary classification.Titanic: Getting Started With R - Part 3: Decision Trees. 10 minutes read. Tutorial index. Last lesson we sliced and diced the data to try and find subsets of the passengers that were more, or less, likely to survive the disaster. We climbed up the leaderboard a great deal, but it took a lot of effort to get there.COVID-19 image data collection ( 🎬 video about the project) Project Summary: To build a public open dataset of chest X-ray and CT images of patients which are positive or suspected of COVID-19 or other viral and bacterial pneumonias ( MERS, SARS, and ARDS .). Data will be collected from public sources as well as through indirect collection ... Exploring Dataset Preparing Dataset Cleaning (removing outliers, normalizing) Visualization Train/Test Split Applying Machine Learning Models Summary Method 2 to solve dataset (Different method to detect glasses) Machine Learning Models that we have applied: KNN Logistic Regression Decision Tree SVM (Linear Kernal) SVM (Non Linear Kernal)FSDKaggle2019 is an audio dataset containing 29,266 audio files annotated with 80 labels of the AudioSet Ontology. FSDKaggle2019 has been used for the DCASE Challenge 2019 Task 2, which was run as a Kaggle competition titled Freesound Audio Tagging 2019. Citation If you use the FSDKaggle2019 dataset or part of it, please cite our DCASE 2019 paper: Eduardo Fonseca, Manoj Plakal, Frederic Font ...Jul 16, 2021 · The dataset features over 1,000 images across 10 separate categories including altar, column, dome (inner), dome (outer), stained glass, vault, flying buttress, apse, and bell tower. Fruits 360 – This dataset features 90,483 images of different fruits and vegetables. The training set features 67,692 images (one fruit or vegetable per image ... BEAGLE is a product available through VRS Consulting, Inc.; 4676 Admiralty Way, Suite 206; Marina Del Ray, CA 90292 (213) 827-7890 and FAX: -3189. In determining whether the glass was a type of "float" glass or not, the following results were obtained (# incorrect answers):This paper presents widely used, avail-. able, open and free E EG datasets available for epilepsy. and seizure diagnos is. A brief compariso n and discus-. sion of open and priv ate datasets has ...CMS Program Statistics. CMS Statistics Reference Booklet. Comprehensive End Stage Renal Disease (ESRD) Care (CEC) Model Public Use Files. Cost Reports. EDI Performance Statistics. Health Plans, Reports, Files and Data. Health Care Information System (HCIS) Data File. Hospital Service Area File. Insight Briefs. May 09, 2021 · The dataset is divided into 5 sets, 4 sets were used for the training and remaining is used for the testing. This process is carried out for all the sets and results are recorded. The average is calculated to evaluate the performance of the model. Further, the Kaggle-2 dataset is used to validate the proposed model. Explore and run machine learning code with Kaggle Notebooks | Using data from ECG Heartbeat Categorization Dataset DA: 96 PA: 28 MOZ Rank: 61 GitHub - YuzheYang/ECG-Heartbeat-Categorization …Jan 05, 2021 · Each dataset will be loaded and the nature of the class imbalance will be summarized. Glass Identification (Glass) Each record describes the chemical content of glass and prediction involves the type of glass. More Details: glass.names; Dataset: glass.csv; Additional Information; Below provides a sample of the first five rows of the dataset. Sep 24, 2020 · using a dataset that has multiple numeric columns in which the values are on different scales. You want to transform the numeric columns so that the values are all on a similar scale based relative to the minimum and maximum values in each column. Which module should you add to the pipeline? 1: Select Columns in a Dataset 2: Normalize Data Download the dataset from the link below, and place the following files in the root: 1- eyeGlasses-faces.mat. 2- non-eyeglasses-faces.mat. Each mat file contains 1294 (227x227 pixels) images picked randomly from SoF and FERET datasets. We have used 1294 images for training and 389 images for testing. That is for each class. To start: -Run demo.m.Jan 12, 2022 · Sample dataset: Daily temperature of major cities. Like Google Dataset Search, Kaggle offers aggregated datasets, but it’s a community hub rather than a search engine. Kaggle launched in 2010 with a number of machine learning competitions, which subsequently solved problems for the likes of NASA and Ford. This paper presents widely used, avail-. able, open and free E EG datasets available for epilepsy. and seizure diagnos is. A brief compariso n and discus-. sion of open and priv ate datasets has ...Glass Dataset - Principal Components Analysis | Kaggle Sunny Lam · 5Y ago · 13,406 views arrow_drop_up Copy & Edit Glass Dataset - Principal Components Analysis Python · Glass Classification Glass Dataset - Principal Components Analysis Comments (1) Run 738.6 s history Version 19 of 19 LicenseNov 16, 2017 · So I successfully split my dataset into Train & Test in a ratio of 70:30 I used this: df_glass ['split'] = np.random.randn (df_glass.shape [0], 1) msk = np.random.rand (len (df_glass)) <= 0.7 train = df_glass [msk] test = df_glass [~msk] print (train) print (test) Now how do I split train and test to X_train and y_train and X_test and y_test ... Glass Multi-Class Classification Dataset. In this tutorial, we will focus on the standard imbalanced multi-class classification problem referred to as "Glass Identification" or simply "glass." The dataset describes the chemical properties of glass and involves classifying samples of glass using their chemical properties as one of six ...The Garbage Classification Dataset contains 6 classifications: cardboard (393), glass (491), metal (400), paper (584), plastic (472) and trash (127). Example pictures for each category are shown below: Size: 83955 KB Price: Free Author: cchangcs Data source: kaggle.com.This is a Glass Identification Data Set from UCI. It contains 10 attributes including id. The response is glass type(discrete 7 values) https://www.kaggle.com/uciml ...Oct 04, 2018 · dataset之coco数据集:coco数据集的简介、安装、使用方法之详细攻略目录coco数据集的简介0、coco数据集的80个类别—yolov3算法采用的数据集1、coco数据集的意义2、coco数据集的特点3、数据集的大小和版本coco数据集的下载1、2014年数据集的下载2、2017的数据集的下载coco数据集的使用方法1、基础用... Glass; Metal; Paper; Plastic; Trash; The dataset is obtained from Kaggle. We will use the opendatasets library to download the dataset. While downloading the dataset, you will be asked to provide your Kaggle username and credentials, which you can obtain using the "Create New API Token" button on your account page on Kaggle.Jan 12, 2022 · Sample dataset: Daily temperature of major cities. Like Google Dataset Search, Kaggle offers aggregated datasets, but it’s a community hub rather than a search engine. Kaggle launched in 2010 with a number of machine learning competitions, which subsequently solved problems for the likes of NASA and Ford. ml & dl & kaggle. Data Science Projects ⭐ 19. Data Science projects on various problem statements and datasets using Data Analysis, Machine Learning Algorithms, Deep Learning Algorithms, Natural Language Processing, Business Intelligence concepts by Python. Kaggle Passenger Screening Challenge Solution ⭐ 19.A machine a learning framework was employed to predict COVID-19 from Chest X-ray images. Unlike the classical approaches for medical image classification which follow a two-step procedure (hand-crafted feature extraction+recognition), we use an end-to-end deep learning framework which directly predicts the COVID-19 disease from raw images without any need of feature extraction.Mar 03, 2022 · This data set is an extension of UCF50 data set which has 50 action categories. With 13320 videos from 101 action categories, UCF101 gives the largest diversity in terms of actions and with the presence of large variations in camera motion, object appearance and pose, object scale, viewpoint, cluttered background, illumination conditions, etc ... Pricing. There's no additional charge for using most Open Datasets. Pay only for Azure services consumed while using Open Datasets, such as virtual machine instances, storage, networking resources, and machine learning. See the pricing page for details. Oct 04, 2018 · dataset之coco数据集:coco数据集的简介、安装、使用方法之详细攻略目录coco数据集的简介0、coco数据集的80个类别—yolov3算法采用的数据集1、coco数据集的意义2、coco数据集的特点3、数据集的大小和版本coco数据集的下载1、2014年数据集的下载2、2017的数据集的下载coco数据集的使用方法1、基础用... Jan 12, 2022 · Sample dataset: Daily temperature of major cities. Like Google Dataset Search, Kaggle offers aggregated datasets, but it’s a community hub rather than a search engine. Kaggle launched in 2010 with a number of machine learning competitions, which subsequently solved problems for the likes of NASA and Ford. An ambiguous something in yaml file. Bookmark this question. Show activity on this post. I am a beginner at computer vision and I'm trying to build a model that can recognizes Egyptian currency. My dataset folder is structured as followed: Data -> train -> images,labels. This is the yaml file I want to modify. Train and validation paths must be ...Mar 11, 2022 · X-ray Kaggle CXR collection, which is composed of 5863 CXRs. 1583 is normal and the remaining shows manifestations of viral and Bacterial Pneumonia. Consists of Shenzhen, China regions (340 normal + 342 tuberculosis) and Montgomery County, USA region (80 normal + 58 Tuberculosis) dataset. In categorising COVID- services addodatared garnet price per caratjetson nx realsense rosbig w online deliverymsdu vs mpdu aggregationmrt full setupkendo datepicker default value todaynot able to login to oracle databasecar giveaways - fd