Description

Image classification models find themselves in different places today, like farms, hospitals, industries, schools, and highways,…

With the creation of much more efficient deep learning models from the early 2010s, we have seen a great improvement in the state of the art in the domain of image classification.

In this course, we shall take you on an amazing journey in which you’ll master different concepts with a step-by-step approach. We shall start by understanding how image classification algorithms work, and deploying them to the cloud while observing best practices. We are going to be using Tensorflow 2 (the world’s most popular library for deep learning, built by Google) and Huggingface

You will learn:

    The Basics of Tensorflow (Tensors, Model building, training, and evaluation)
    Deep Learning algorithms like Convolutional neural networks and Vision Transformers
    Evaluation of Classification Models (Precision, Recall, Accuracy, F1-score, Confusion Matrix, ROC Curve)
    Mitigating overfitting with Data augmentation
    Advanced Tensorflow concepts like Custom Losses and Metrics, Eager and Graph Modes and Custom Training Loops, Tensorboard
    Machine Learning Operations (MLOps) with Weights and Biases (Experiment Tracking, Hyperparameter Tuning, Dataset Versioning, Model Versioning)
    Binary Classification with Malaria detection
    Multi-class Classification with Human Emotions Detection
    Transfer learning with modern Convnets (Vggnet, Resnet, Mobilenet, Efficientnet)
    Model Deployment (Onnx format, Quantization, Fastapi, Heroku Cloud)

If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!

This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.

Enjoy!!!
Who this course is for:

    Beginner Python Developers curious about Applying Deep Learning for Computer vision
    Deep Learning for Computer vision Practitioners who want gain a mastery of how things work under the hood
    Anyone who wants to master deep learning fundamentals and also practice deep learning for image classification using best practices in TensorFlow.
    Computer Vision practitioners who want to learn how state of art image classification models are built and trained using deep learning.
    Anyone wanting to deploy image classification Models
    Learners who want a practical approach to Deep learning for image classification

Requirements

    Basic Knowledge of Python
    Access to an internet connection, as we shall be using Google Colab (free version)

Last Updated 2/2023