Dive into the second lecture of a four-part series on machine learning, led by Dr. Abdelrahman Kotb. Explore the critical role of data in machine learning, covering topics such as data collection, preprocessing, and exploratory data analysis. Gain insights into the importance of quality data and learn the fundamentals of Python programming for machine learning applications. This 35-minute lecture, part of PioPetro's Summer Training 2024, bridges concepts from petroleum engineering, energy transition, geology, and petrophysics with machine learning techniques. Recap key points from the first lecture before delving into new material, and get a preview of upcoming topics for lectures 3 and 4. Conclude with essential takeaways and a Q&A session to solidify your understanding of machine learning principles in the context of energy and earth sciences.
Overview
Syllabus
Introduction
Lecture 1 recap
Importance of data
Collecting data
Data preprocessing
exploratory data analysis
introduction to python
Lecture 3 topics
Lecture 4 topics
Takeaways
Questions
Taught by
PioPetro
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