Introduction to Data Analysis in Python  099102





Lecture 
Exercise 
Laboratory 
Project or Seminar 
House Work 
Weekly Hours 
2 





Determination of the grade according to progress during the semester and the submission of the final thesis
Prerequisites:
    Statistics for Managers 
098740
 
Python. Our Focus Will Be on Classification Algorithms (Svm, Logistic Regression), Regression Algorithms (Linear Regression, Lasso), and Ensemble Methods (Random Forest), in Addition to Model Evaluation Techniques. Moreover, We Will Explore the Software Tools That Consitute the Python Data Science Ecosystem. This Course Introduces Students to Machine
Learning Outcomes
At the End of the Course the Student Will Know to Write Basic Code in Python. Use Standart Data Science Packages in Python, E.G. Pandas, Numpy and ScikitLearn. Conduct Exploratory Data Analysis. Employ Predictive Algorithms for Regression and Classification. Understand and Analyze the Challenges in Model Evaluation.
TextbooksPublished  Publisher  Authors  Book 

2016  o'reilly media  j. vanderplas  pyton data science handbook: essential tools for working with datap 
Created in 06/03/2021 Time 01:36:38