Machine learning and big data : concepts, algorithms, tools and applications /
"Machine learning with big data technologies create new opportunities to understand the various data process related to medical or environmental aspects of agriculture. Machine learning as a field is now incredibly pervasive, with applications spanning from business intelligence to homeland sec...
Saved in:
| Other Authors: | , , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, NJ :
Wiley-Scrivener,
2020.
|
| Subjects: | |
| Online Access: | CONNECT CONNECT |
| LEADER | 04781nam a22005411i 4500 | ||
|---|---|---|---|
| 001 | in00006302855 | ||
| 006 | m |o d | | ||
| 007 | cr |n||||||||| | ||
| 008 | 230113t20202020njua ob 001 0 eng d | ||
| 005 | 20230123155107.0 | ||
| 035 | |a (NhCcYBP)e792ad23fda947dab6477b3838b647ec9781119654834 | ||
| 035 | |a 1wileyeba9781119654834 | ||
| 040 | |a NhCcYBP |b eng |e rda |c NhCcYBP | ||
| 020 | |a 9781119654834 | ||
| 020 | |a 1119654831 (electronic bk.) | ||
| 020 | |z 9781119654742 | ||
| 020 | |z 1119654742 | ||
| 050 | 4 | |a Q325.5 |b .M3382 2020 | |
| 082 | 0 | 4 | |a 006.3/1 |2 23 |
| 245 | 0 | 0 | |a Machine learning and big data : |b concepts, algorithms, tools and applications / |c edited by Uma N. Dulhare, Khaleel Ahmad and Khairol Amali Bin Ahmad. |
| 264 | 1 | |a Hoboken, NJ : |b Wiley-Scrivener, |c 2020. | |
| 264 | 4 | |c ©2020 | |
| 300 | |a 1 online resource (xx, 512 pages : : |b illustrations.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Section 1: Theoretical Fundamentals -- Mathematical Foundation / Afroz and Basharat Hussain -- Theory of Probability / Parvaze Ahmad Dar and Afroz -- Correlation and Regression / Mohd. Abdul Haleem Rizwan -- Section 2: Big Data and Pattern Recognition -- Data Preprocess / Md. Sharif Hossen -- Big Data / R. Chinnaiyan -- Pattern Recognition Concepts / Ambeshwar Kumar, R. Manikandan and C. Thaventhiran -- Section 3: Machine Learning: Algorithms & Applications -- Machine Learning / Elham Ghanbari and Sara Najafzadeh -- Performance of Supervised Learning Algorithms on Multi-Variate Datasets / Asif Iqbal Hajamydeen and Rabab Alayham Abbas Helmi -- Unsupervised Learning / M. Kumara Swamy and Tejaswi Puligilla -- Semi-Supervised Learning / Manish Devgan, Gaurav Malik and Deepak Kumar Sharma -- Reinforcement Learning / Amandeep Singh Bhatia, Mandeep Kaur Saggi, Amit Sundas and Jatinder Ashta -- Application of Big Data and Machine Learning / Neha Sharma, Sunil Kumar Gautam, Azriel A. Henry and Abhimanyu Kumar -- Section 4: Machine Learning's Next Frontier -- Transfer Learning / Riyanshi Gupta, Kartik Krishna Bhardwaj and Deepak Kumar Sharma -- Section 5: Hands-On and Case Study -- Hands on MAHOUT-Machine Learning Tool / Uma N. Dulhare and Sheikh Gouse -- Hands-On H2O Machine Learning Tool / Uma N. Dulhare, Azmath Mubeen and Khaleel Ahmed -- Case Study: Intrusion Detection System Using Machine Learning / Syeda Hajra Mahin, Fahmina Taranum and Reshma Nikhat -- Inclusion of Security Features for Implications of Electronic Governance Activities / Prabal Pratap and Nripendra Dwivedi. | |
| 520 | |a "Machine learning with big data technologies create new opportunities to understand the various data process related to medical or environmental aspects of agriculture. Machine learning as a field is now incredibly pervasive, with applications spanning from business intelligence to homeland security from analyzing biochemical interactions to structural monitoring of aging bridges, and from emissions to astrophysics, etc. As we are entering the Industrial Revolution 4.0, BD/ML applications, in combination with IoT/Cloud technologies, are fundamentally changing any domain-specific industry. Development of this field is very important because it can help to enhance human life by the automation system, which in turn has far-reaching effects for economic, psychological, educational and organizational improvements to the way we work, teach, learn and care for ourselves and each other"-- |c Provided by publisher. | ||
| 588 | |a Description based on print version record. | ||
| 590 | |a Wiley EBA | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Big data. | |
| 700 | 1 | |a Dulhare, Uma N., |e editor. | |
| 700 | 1 | |a Ahmad, Khaleel, |e editor. | |
| 700 | 1 | |a Khairol Amali Bin Ahmad, |e editor. | |
| 710 | 2 | |a John Wiley & Sons, Ltd., |e publisher. | |
| 730 | 0 | |a WILEYEBA | |
| 776 | 0 | 8 | |i Online version: |t Machine learning and big data |d Hoboken, NJ : Wiley-Scrivener, 2020 |z 9781119654810 |w (DLC) 2020031698 |
| 776 | 0 | 8 | |c Original |z 9781119654742 |z 1119654742 |w (DLC) 2020031697 |
| 856 | 4 | 0 | |u https://ezproxy.mtsu.edu/login?url=https://onlinelibrary.wiley.com/book/10.1002/9781119654834 |z CONNECT |3 Wiley |t 0 |
| 949 | |a ho0 | ||
| 975 | |p Wiley UBCM All Titles Through 2022 | ||
| 976 | |a 6005002 | ||
| 998 | |a wi |d z | ||
| 999 | f | f | |s d781777a-44d0-4911-ae54-7ec0e98c4155 |i 03fe1fb8-5d21-4938-89aa-be5e3bc010b5 |t 0 |
| 952 | f | f | |a Middle Tennessee State University |b Main |c James E. Walker Library |d Electronic Resources |t 0 |e Q325.5 .M3382 2020 |h Library of Congress classification |
| 856 | 4 | 0 | |3 Wiley |t 0 |u https://ezproxy.mtsu.edu/login?url=https://onlinelibrary.wiley.com/book/10.1002/9781119654834 |z CONNECT |
