Machine learning and data science : fundamentals and applications

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Başlık:

Yazar:

Agrawal, Prateek, editor.

ISBN:

9781119776499

9781119776475

9781119776482

Fiziksel Tanımlama:

1 online resource.

Seri:

Advances in data engineering and machine learning

İçerik:

Machine Learning: An Introduction to Reinforcement Learning / Sheikh Amir Fayaz, S Jahangeer Sidiq, Majid Zaman, Muheet Ahmed Butt -- Data Analysis Using Machine Learning: An Experimental Study on UFC / Prashant Varshney, Charu Gupta, Palak Girdhar, Anand Mohan, Prateek Agrawal, Vishu Madaan -- Dawn of Big Data with Hadoop and Machine Learning / Balraj Singh, Harsh Kumar Verma -- Industry 4.0: Smart Manufacturing in Industries - The Future / K Bhavana Raj -- COVID-19 Curve Exploration Using Time Series Data for India / Apeksha Rustagi, Divyata, Deepali Virmani, Ashok Kumar, Charu Gupta, Prateek Agrawal, Vishu Madaan -- A Case Study on Cluster Based Application Mapping Method for Power Optimization in 2D NoC / Aravindhan Alagarsamy, Sundarakannan Mahilmaran -- Healthcare Case Study: COVID19 Detection, Prevention Measures, and Prediction Using Machine Learning & Deep Learning Algorithms / Devesh Kumar Srivastava, Mansi Chouhan, Amit Kumar Sharma -- Analysis and Impact of Climatic Conditions on COVID-19 Using Machine Learning / Prasenjit Das, Shaily Jain, Shankar Shambhu, Chetan Sharma -- Application of Hadoop in Data Science / Balraj Singh, Harsh K Verma -- Networking Technologies and Challenges for Green IOT Applications in Urban Climate / Saikat Samanta, Achyuth Sarkar, Aditi Sharma -- Analysis of Human Activity Recognition Algorithms Using Trimmed Video Datasets / Disha G Deotale, Madhushi Verma, P Suresh, Divya Srivastava, Manish Kumar, Sunil Kumar Jangir -- Solving Direction Sense Based Reasoning Problems Using Natural Language Processing / Vishu Madaan, Komal Sood, Prateek Agrawal, Ashok Kumar, Charu Gupta, Anand Sharma, Awadhesh Kumar Shukla -- Drowsiness Detection Using Digital Image Processing / G Ramesh Babu, Chinthagada Naveen Kumar, Maradana Harish.

Özet:

MACHINE LEARNING AND DATA SCIENCE Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia. Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms. These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

Notlar:

John Wiley and Sons

Konu Terimleri:

Machine learning.

Data mining.

Apprentissage automatique.

Exploration de données (Informatique)

Information Technology.

COMPUTERS.

Data mining

Machine learning

Aprenentatge automàtic.