Category: image-classification
-
A Refined Training Recipe for Fine-Grained Visual Classification
A Refined Training Recipe for Fine-Grained Visual Classification How FGVC aims to recognize images belonging to multiple subordinate categories of a super-category The post A Refined Training Recipe for Fine-Grained Visual Classification appeared first on Towards Data Science. Ahmed Belgacem Go to original source
-
Learnings from a Machine Learning Engineer — Part 6: The Human Side
Learnings from a Machine Learning Engineer — Part 6: The Human Side In my previous articles, I have spent a lot of time talking about the technical aspects of an Image Classification problem from data collection, model evaluation, performance optimization, and a detailed look at model training. These elements require a certain degree of in-depth expertise, and they (usually) have well-defined…
-
Learnings from a Machine Learning Engineer — Part 5: The Training
Learnings from a Machine Learning Engineer — Part 5: The Training In this fifth part of my series, I will outline the steps for creating a Docker container for training your image classification model, evaluating performance, and preparing for deployment. AI/ML engineers would prefer to focus on model training and data engineering, but the reality…
-
Learnings from a Machine Learning Engineer — Part 3: The Evaluation
Learnings from a Machine Learning Engineer — Part 3: The Evaluation In this third part of my series, I will explore the evaluation process which is a critical piece that will lead to a cleaner data set and elevate your model performance. We will see the difference between evaluation of a trained model (one not yet in…
-
Learnings from a Machine Learning Engineer — Part 1: The Data
Learnings from a Machine Learning Engineer — Part 1: The Data It is said that in order for a machine learning model to be successful, you need to have good data. While this is true (and pretty much obvious), it is extremely difficult to define, build, and sustain good data. Let me share with you…
-
Learnings from a Machine Learning Engineer — Part 4: The Model
Learnings from a Machine Learning Engineer — Part 4: The Model In this latest part of my series, I will share what I have learned on selecting a model for Image Classification and how to fine tune that model. I will also show how you can leverage the model to accelerate your labelling process, and…
-
Learnings from a Machine Learning Engineer — Part 3: The Evaluation
Learnings from a Machine Learning Engineer — Part 3: The Evaluation Practical insights for a data-driven approach to model optimization Continue reading on Towards Data Science » David Martin Go to original source
-
Learnings from a Machine Learning Engineer — Part 2: The Data Sets
Learnings from a Machine Learning Engineer — Part 2: The Data Sets Practical insights for a data-driven approach to model optimization Continue reading on Towards Data Science » David Martin Go to original source
-
Learnings from a Machine Learning Engineer — Part 1: The Data
Learnings from a Machine Learning Engineer — Part 1: The Data Practical insights for a data-driven approach to model optimization Continue reading on Towards Data Science » David Martin Go to original source