Custom Face Swap using Python and OpenCV & Deepfake Image Animation using 'First Order Motion Model' paper in Colab

Quick Starter for Optical Character Recognition, Image Recognition Object Detection and Object Recognition using Python

Quick Starter for Optical Character Recognition, Image Recognition Object Detection and Object Recognition using Python

YOLO: Pre-Trained Coco Dataset and Custom Trained Coronavirus Object Detection Model with Google Colab GPU Training

YOLO: Pre-Trained Coco Dataset and Custom Trained Coronavirus Object Detection Model with Google Colab GPU Training

Learn how to compute matrix algebra using R and Rcpp for high-performance data analysis.

Study methods for processing and analyzing natural language data for various AI applications.

This course highlights the artchitecture, functionality, and troubleshooting strategies using IBM Cloud Clode Engine.

Flink is a stateful, tolerant, and large-scale system with excellent latency and throughput characteristics. It works with bounded and unbounded datasets using the same underlying stream-first architecture, focusing on streaming or unbounded data.

Much real-world data is available in streams; from self-driving car sensors to weather monitors. Apache Spark 2 is a strong analytics engine with first-class support for streaming operations using micro-batch and continuous processing.

In this course, you will learn about the Spark based Azure Databricks platform. You will see how Spark Structured Streaming processing model works, and then use it to build end-to-end production ready streaming pipeline on Azure Databricks platform.

In this course, you will learn how you can use the Amazon Kinesis Data Analytics service to process streaming data using both the Apache Flink runtime and the SQL runtime. You will integrate your streaming applications with Kinesis Data Streams, Kinesis Data Firehose Delivery streams, and Amazon’s S3.