Introduction to Jupyter Notebook

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (31)

Page 3 of 4

Covers the basics of Matplotlib for 2D graphic representation in Python, including plotting data and visualizing functions.

Python Complement: Numpy, Scipy, Matplotlib

Covers advanced Python topics like numpy operations, scipy linear algebra, and matplotlib for creating figures.

Data Wrangling with Hadoop: Storage Formats and Hive

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.

Big Data Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Introduction to Machine Learning: Course Overview and Basics

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Numerical Methods: Stopping Criteria, SciPy, and Matplotlib

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Introduction to Renku

Introduces Renku, a platform for collaborative data science, emphasizing reproducibility, shareability, reusability, and security.

Data Science with Python: Numpy Basics

Introduces the basics of Numpy, a numerical computing library in Python, covering advantages, memory layout, operations, and linear algebra functions.

Big Data Ecosystems: Technologies and Challenges

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.

Distributed Version Control with Git

Explores Git's distributed version control, covering conflict resolution, collaboration management, and merging in software projects.