Name: Hamza Nasir (The Big Data Lad)
Type: User
Company: Systems Limited (Visionet Systems Inc)
Bio: The Big Data Lad - Big Data Engineer at Systems Limited π₯ | Data Geek π©π»βπ» | Keen about Apache Spark, Kafka, NiFi, Airflow, DataOps, ML, & Cloud Computing
Location: Islamabad, Pakistan
Blog: BigDataLad.com
Hamza Nasir (The Big Data Lad)'s Projects
Adjusted R-Squared is a metric for regression just like R-Squared Coefficient but Adjusted R-Squared also takes into account the dimentions which actually play their role in improving the model.
A new recursive MergeSort++ which is a variant of classical merge sort.
Analysing the leading death causes in the United States.
A Data Engineering & Machine Learning Knowledge Hub
Generate Scala case class definitions from Avro schemas
Curated List of Awesome Django Admin Panel Articles, Libraries/Packages, Books, Themes, Videos, Resources.
A curated list of awesome frameworks, libraries and software for the Java programming language.
A curated list of awesome Python frameworks, libraries, software and resources
π€ Build your own (insert technology here)
Apache Camel Kafka Connector Examples
In this kernel, we are going to predict whether a credit card is fraud or not using Machine Learning.
This repo contains commands that data engineers use in day to day work.
An ultra-simplified explanation to design patterns
Curated list of design and UI resources from stock photos, web templates, CSS frameworks, UI libraries, tools and much more
A cheatsheet (or really more of a reference) for when I am solving the worlds problems in the Django shell
Combined Zookeeper and Kafka centos7 docker image
A collection of online resources to help you on your DevOps journey.
Apache Kafka and Confluent Platform examples and demos
Performed EDA on the bank's customer churn data and tried to get some insights.
Initial Commit, Data Cleaning done but analysis is pending
Let's say we want to identify certain groups of Facebook users based on their behavior. Some facebook users might not react on the posts. Some people may 'like' react more and use other reactions like 'love' or 'wow' to a very minute extent. Some people may share posts a lot while some may not. Some only react and not comment on posts. Some may comment but react much, etc. We are going to identify such groups with the help of machine learning.
JSON to JSON transformation library written in Java.
Plumb a PDF for detailed information about each char, rectangle, line, et cetera βΒ and easily extract text and tables.
Predicting if a candidate student will get admission or not in a particular university using Machine Learning algorithms in Python.
Prediction of Train Ticket Prices in Spain using Supervised Machine Learning Algorithms and then comparing R-Squared coefficient to select the most well-suited model for deployment.
PySpark Cheat Sheet - learn PySpark and develop apps faster