Top.Mail.Ru
Vadim Demichev - Analyzing Big Data with Machine Learning Methods - online library of lections from ProAgro Lectorium
Sign in
Become speaker
Lectures Speakers About Contacts
Back
Lectures Welcome to Pro Agro Lectorium Production of mineral fertilizers Primary macronutrients Secondary macronutrients Micronutrients Climate smart agriculture Plant health Crop nutrition systems Livestock breeding Green chemistry for life Economics of agriculture Ecology of agriculture Forest melioration Soil Contamination by Heavy Metals Soil Contamination by other Pollutants Silicon Soil health and fertility PhosAgro fertilizers Digital agriculture Agricultural crops Global food security
Back
Back
En
Русский English Português
En
Русский English Português
Sign in
Become speaker
Sign in
Become speaker
Home Lectures Digital agriculture

Analyzing Big Data with Machine Learning Methods

Lecture outline
  • Introduction to machine learning
  • Essential Python libraries for machine learning
  • Model building process
V. Demichev - Analyzing Big Data with Machine Learning Methods.pdf
pdf — 2 Мб
Speaker
Vadim Demichev
Candidate of Economic Sciences, Associate Professor of the Department of Statistics and Cybernetics of the Russian State Agrarian University — Moscow Timiryazev Agricultural Academy
About the speaker

Cookie policy

This site uses analytics cookies to optimize its performance and to improve the user experience on the website and statistic cookies to track statistics of the visiting website. By clicking the button «Accept All», you agree with our use of cookies in accordance with our Cookie Policy. You can manage cookies, which are placed on your devices (tablet, smartphone, PC, etc.): delete cookies, set permissions for them, and withdraw your consent to our use of cookies. You can always change your cookie settings on Terms of usage page.

Analytical and statistical cookies

These files allow us to analyze your experience with our Website, increase the performance of the website and track the statistics of your visits to our Website. This information helps us to determine the most popular sections of our Website and optimize it to make it easier for you to find the information you need.

Help