Calicut University, Calicut is offering Master of Technology (MTech Machine Learning). In this section, learn about the Master of Technology (MTech Machine Learning) course at Calicut University, Calicut
B.E./B.Tech. or equivalents with minimum 50% are eligible to apply to this course.
MML10 101 Probability and Statistics
MML10 102 Linear Algebra
MML10 103 Pattern Recognition
MMLIo 104 Image Processing
MMLIo 105 (A) Numerical Methods (Elective I)
MMLIo 105 (B) Advanced Digital SiSnal Processing (Elective I)
MMLIo 105 (C) Optimisation Techniques (Elective I)
MMLIo 105 (D) Information Theory and Learning Algorithms (Elective I)
MMLIo1os (E) Artificial Intelligence (Elective I)
MMLIo 106 (P) Seminar I
MML1O ro7 (P) Machine Learning Lab 1
MML10 201 Machine Learning
MML10 202 Imbalanced Learning
MML10 203 Soft computing
MML1O 204 (A) Introduction to NLp (Elective II)
MMLfo 204 (B) Sparse Signal Processing (Elective II)
MMLIo 204 (C) Machine Translation (Elective II)
MMLIo 204 (D) Speech and Audio Processing (Elective II)
MMLIo 205 (A) Machine Learning for Computer vision (Elective III)
MML1O 205 (B) Data Mining (Elective III)
MML1O 205 (C) Optimization Methods in Machine Learning (Elective III)
MML1O 206 (P) Seminar II
MMLIo 207 (P) Machine Learning Lab 2
MMLIo 301 (A) Advanced Topics in Machine Learning (Elective IV)
MML10 3ol (B) Speech Processing in Mobile Environments (Elective IV)
MMLIo 301 (C) Research Methodolory (Elective IV)
MMLIo 302 (A) Reinforcement Learning (Elective V)
MMLIo 302 (B) Machine Learning for NLP (Elective V)
MMLIo 302 (C) Neural Networks for Machine Learning (Elective V)
MML1o 303 Industrial Training
MMLIo 304 (P) Master Research Project Phase 1
MMLl0 401 (P) Master Research Project Phase z
Note: The above courses are picked automatically by the website for indicative purpose only. However, students are requested to check with the University for the similarity of the course or for any other information in regard to the course.
Syllabus presented on this page is indicative and for general information only. The syllabus / course information listed may not be exhuastive. Students / Visitors are advised to contact the University directly for the official, detailed and accurate Syllabus, Transcripts and other information. List of course names mentioned here is partial and are not comprehensive and the institution would be offering many other courses than those mentioned on this page.
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