Academic achievement is a multifaceted outcome influenced by a multitude of factors spanning across educational, socioeconomic, and individual characteristics. Understanding the key determinants of students’ academic performance is paramount for educato
Kaggle dataset is used in this paper and two phase of experiment have been conducted, single classifier without GAFS, and single classifier with GAFS. Results from the experiments show that, the accuracy of the proposed GAFS for classification makes an impressive performance in predicting student ...
The main focus is performance. When we deal with sample or training data in nlp, we quickly run out of memory. Therefore every implementation in this module is written as stream to only hold that data in memory that is currently processed at any step. Julia high-level, high-performance ...
Interpretable Machine Learning With Python: Learn to Build Interpretable High-Performance Models With Hands-On Real-World Examples Responsible AI (Hall, P., Chowdhury, R., 2023) Governance Safety Drift Marcus, G. F. (2024). Taming Silicon Valley: How We Can Ensure That AI Works for Us. MIT...
01 Surface Pro 4 Drivers and Firmware This device has reached the End of Servicing. The following packages are no longer being updated with latest drivers and firmware. 02 Kaggle Cats and Dogs Dataset Web services are often protected with a challenge that's supposed to be easy for people to...
The dataset was collected from the Kaggle repository. To analyze the dataset, different classification algorithms were applied like decision tree, random forest, SVM classifier, SGD classifier, AdaBoost classifier, and LR classifier. This research revealed that random forest achieved ...
Explore and run machine learning code with Kaggle Notebooks | Using data from Students' Academic Performance Dataset
Reference [16] used multiple regression, and [69] used SVM and LR to compare the performance of the proposed model. In both studies [16,69], LSTM outperformed other models. Vijayalakshmi et al. trained and tested their network using the Kaggle dataset [70] and used a variety of ...
performance. Firstly, three single classifiers including a Multilayer Perceptron (MLP), J48, and PART were observed along with three well-established ensemble algorithms encompassing Bagging (BAG), MultiBoost (MB), and Voting (VT) independently. To further enhance the performance of the above...
Analyze their performance.Dataset link: https://www.kaggle.com/datasets/balaka18/email-spam-classification-dataset-csv B3 Given a bank customer, build a neural network-based classifier that can determine whether they will leave or not in the next 6 months.Dataset Description: The case study is ...