Machine Learning in IoT Era

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Related lectures (32)

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Data, big data, clouds and IoT

Explores data representation, databases, cloud computing, and challenges in the cloud environment.

Introduction to R Programming for Genetics & Genomics

Introduces a course on Genetics & Genomics, focusing on R programming with interactive exercises.

Data Science Fundamentals

Covers the fundamentals of data science, the scientific method evolution, the role of a data scientist, and the significance of data as the new oil.

Neural Networks Recap: Activation Functions

Covers the basics of neural networks, activation functions, training, image processing, CNNs, regularization, and dimensionality reduction methods.

Cache Memory

Explores cache memory design, hits, misses, and eviction policies in computer systems, emphasizing spatial and temporal locality.

Multiclass Classification

Covers the concept of multiclass classification and the challenges of linearly separating data with multiple classes.

Advanced Spark Optimization Techniques: Managing Big Data

Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.

Handling Data: Intro to Pandas

Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.

Digital Transformation: Solutions and Data

Explores digital transformation opportunities, big data, analytics, and technology innovations in business and research.

Data Driven Science: MODNet Methodology

Explores the MODNet methodology for material property predictions, emphasizing feature selection and supervised learning.