Summary of Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer, by Benji Peng et al.
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer
by Benji Peng, Xuanhe Pan, Yizhu Wen, Ziqian Bi, Keyu Chen, Ming Li, Ming Liu, Qian Niu, Junyu Liu, Jinlang Wang, Sen Zhang, Jiawei Xu, Pohsun Feng
First submitted to arxiv on: 25 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Machine learning educators can leverage this book to teach students about the role of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in driving progress in big data analytics and management. The book offers a simplified explanation of deep learning concepts, accompanied by intuitive visualizations and practical case studies that demonstrate how neural networks and models like Convolutional Neural Networks (CNNs), Transformers, GPT, ResNet, BERT, and YOLO work. Applications are highlighted across fields such as natural language processing, image recognition, and autonomous driving. Pre-trained models are emphasized for their ability to enhance model performance and accuracy, with instructions on how to apply them in real-world scenarios. The book also covers key big data management technologies like SQL and NoSQL databases, Apache Hadoop, and Spark, explaining their importance in managing vast amounts of data. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This book helps students understand the power of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in managing big data. The book explains deep learning concepts simply, with pictures and real-life examples that show how neural networks work. It also talks about different AI models like CNNs, Transformers, GPT, ResNet, BERT, and YOLO, and shows how they’re used in areas like understanding language, recognizing images, and driving cars. The book also covers big data management tools like databases and computer frameworks, showing how they help manage huge amounts of information. |
Keywords
» Artificial intelligence » Bert » Deep learning » Gpt » Machine learning » Natural language processing » Resnet » Yolo
