Ementorhub

What you'll learn

Understand at a high-level the types of problems computer vision may solve

Understand some of the key concepts and model architectures typically used using computer vision

Skills you'll gain

Cloud API

Image Analysis

Tensorflow

Artificial Neural Networks

Machine Learning Methods

Small Data

Feature Engineering

Applied Machine Learning

Computer Vision

Data Processing

Supervised Learning

Deep Learning

Google Cloud Platform

Artificial Intelligence and Machine Learning (AI/ML)

There are 7 modules in this course

The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data. The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models. Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.

Introduction to Computer Vision and Pre-built ML Models for Image Classification

Vertex AI and AutoML Vision on Vertex AI

Custom Training with Linear, Neural Network and Deep Neural Network models

Convolutional Neural Networks

Dealing with Image Data

Summary