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Titlebook: Conference Proceedings of ICDLAIR2019; Meenakshi Tripathi,Sushant Upadhyaya Conference proceedings 2021 The Editor(s) (if applicable) and

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樓主: 人工合成
11#
發(fā)表于 2025-3-23 12:32:41 | 只看該作者
2367-3370 ce on Deep Learning, Artificial Intelligence and Robotics he.This proceedings book includes the results from the International Conference on Deep Learning, Artificial Intelligence and Robotics, held in Malaviya National Institute of Technology, Jawahar Lal Nehru Marg, Malaviya Nagar, Jaipur, Rajasth
12#
發(fā)表于 2025-3-23 16:29:36 | 只看該作者
https://doi.org/10.1007/978-3-030-87821-4en done on analytic of crime demographics and geographic prior to this project. The unfortunate, frequent nature of crime, and the fact that it often follows a geographic and demographic pattern which requires constant updation makes this data set an excellent choice for online learning based models for analytics.
13#
發(fā)表于 2025-3-23 20:06:28 | 只看該作者
Encounters between East and Westo Fake news detection such as Naive Bayes Classifier, Decision tree and has proposed a novel approach for Fake news detection by implementing Association rule based classification ARBC). Experimental results has indicated notable improvement in detection accuracy.
14#
發(fā)表于 2025-3-23 22:48:39 | 只看該作者
15#
發(fā)表于 2025-3-24 03:56:37 | 只看該作者
16#
發(fā)表于 2025-3-24 10:12:22 | 只看該作者
https://doi.org/10.1007/978-3-531-93348-1 of our data. Different data visualizations in below paper are done using different perplexity values of t-SNE. Pre-processing and vectorization are done accordingly for different features and numerical features are standardized before giving it to t-SNE.
17#
發(fā)表于 2025-3-24 12:17:06 | 只看該作者
18#
發(fā)表于 2025-3-24 17:48:31 | 只看該作者
Text Visualization Using t-Distributed Stochastic Neighborhood Embedding (t-SNE), of our data. Different data visualizations in below paper are done using different perplexity values of t-SNE. Pre-processing and vectorization are done accordingly for different features and numerical features are standardized before giving it to t-SNE.
19#
發(fā)表于 2025-3-24 19:23:57 | 只看該作者
Stock Price Prediction Using Recurrent Neural Network and Long Short-Term Memory,f using the data for a specific model, latent dynamics of the data-set is identified with the help of deep learning algorithms. In the proposed model, the price of Google Stock is predicted using two deep learning models with the least possible error. We are applying the Recurrent Neural Network for predicting the price on a short term basis.
20#
發(fā)表于 2025-3-25 02:13:06 | 只看該作者
Conference proceedings 2021 National Institute of Technology, Jawahar Lal Nehru Marg, Malaviya Nagar, Jaipur, Rajasthan, 302017. ..The scope of this conference includes all subareas of AI, with broad coverage of traditional topics like robotics, statistical learning and deep learning techniques. However, the organizing commit
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