Study Guide


Content of Studies »

Course Search

Description


IN00CR47 Basics of Machine Learning (5 cr)
Prerequisites Not applicable
Objectives ? A student knows what machine learning can do and what it can not do. Student knows some topical machine learning solutions.
? A student knows what mathematics is typically required for implementing machine learning solutions and student can implement matrix multiplication
and gradient decent algorithm with Python.
? A student knows what tools are available for machine learning solutions and student can implement simple Python programs using numPy
and Matplotlib Python modules.
? A student understands how neural network is used to identify numbers from gray scale pictures.
Content ? Introduction to machine learning
? Mathematics (matrices, derivative and gradient) for understanding how machines learn
? Programming tools (Python) for implementing machine learning algorithms
? Machine learning "hello world" algorithm for identifying numbers from gray scale pictures with neural network.
Recommended optional programme components If necessary, the student advisor will recommend optional programme components for each student based on their individual study plan.
Accomplishment methods Not applicable
Execution methods Not applicable
Materials Not applicable
Literature Not applicable
Evaluation Criteria Not applicable
Assessment Frameworks Arviointikehikko
Further Information Not applicable
Links Arviointikehikko

Implementations


Show old implementations
  • 01.09.2019 - 31.05.2020 (IN00CR47-3001 | YHT19S, YHT20K)
17.11.2019 11:22:10
Administrator of the page: Johanna Huttunen  |  Page updated: April 17th, 2018