Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer
<|reference_start|>Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer: This book explores the role of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in driving the progress of big data analytics and management. The book focuses on simplifying the complex mathematical concepts behind deep learning, offering intuitive visualizations and practical case studies to help readers understand how neural networks and technologies like Convolutional Neural Networks (CNNs) work. It introduces several classic models and technologies such as Transformers, GPT, ResNet, BERT, and YOLO, highlighting their applications in fields like natural language processing, image recognition, and autonomous driving. The book also emphasizes the importance of pre-trained models and how they can enhance model performance and accuracy, with instructions on how to apply these models in various real-world scenarios. Additionally, it provides an overview of key big data management technologies like SQL and NoSQL databases, as well as distributed computing frameworks such as Apache Hadoop and Spark, explaining their importance in managing and processing vast amounts of data. Ultimately, the book underscores the value of mastering deep learning and big data management skills as critical tools for the future workforce, making it an essential resource for both beginners and experienced professionals.<|reference_end|>
@article{peng2024deep,
    title={Deep Learning and Machine Learning, Advancing Big Data Analytics and
  Management: Handy Appetizer},
    author={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},
    journal={arXiv preprint arXiv:2409.17120},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.17120},
    primaryClass={cs.CL cs.LG}
}