Spark and Python for Big Data with PySpark

What I have Learned:

Introduction to Spark DataFrames: I learned the fundamentals of Spark DataFrames, which enabled me to work with structured and tabular data efficiently. Through various operations, transformations, and manipulation techniques, I acquired the skills to process and analyze data effectively.

Machine Learning with MLlib: I ventured into the field of machine learning with the MLlib library in Spark. Through practical examples and hands-on exercises, I gained a solid understanding of linear regression and logistic regression. I also learned evaluation techniques to ensure accurate model predictions.

Tree Methods: I acquired knowledge about decision tree-based algorithms, including decision trees and random forests. By understanding the underlying theory and exploring practical implementations using Spark's MLlib library, I gained proficiency in classification and regression tasks.

K-means Clustering: I explored the fascinating world of unsupervised learning through the K-means clustering algorithm. By studying the theory behind it and applying it to real-world datasets using Spark, I gained insights into how to group data based on patterns and interpret the results.

Introduction to Recommender Systems: I discovered the concepts and techniques behind recommender systems. These systems enable personalized suggestions based on user preferences. I obtained an overview of the building blocks and methodologies used to create effective recommendation engines.

Natural Language Processing (NLP): I dived into the exciting field of natural language processing using Spark. By learning about NLP tools, such as tokenization, stemming, and text classification, I gained the ability to perform advanced text analysis and gain valuable insights from textual data. The code-along project provided a hands-on experience in applying NLP techniques.

Introduction to Spark Streaming: I explored the world of real-time data processing through Spark Streaming. By understanding the basics of streaming data processing and learning to work with streaming data in Spark, I acquired the skills to handle and analyze data in real-time scenarios.

You can find course codes and materials by clicking on the following button:

• Github Link