The Role of Loss Functions | Most Common Loss Functions in Machine Learning | Explained!
๐ฅ Loss Functions are a key topic in machine learning. Those functions provide a metric of how good your model is performing. Usually, it is a number going from 0 to infinity. You try to optimize the model in a way, that it eventually reaches 0 (which never happens). Mostly loss functions are used either for regression or classification tasks. Regression losses include mean absolute error (MAE), mean squared error (MSE) or other functions that compare continuous values. For classification, on the other hand, we have cross-entropy that is the most popular one. Keep in mind that some ML algorithโฆ
Watch on YouTube โ
(saves to browser)
Chapters (12)
Introduction.
0:04
What is loss function?
0:13
Types of loss functions.
0:17
Regression loss functions (MAE, MSE)
0:39
MSE vs. MAE.
1:02
Classification loss functions (cross-entropy)
1:16
Binary cross-entropy: an example.
1:27
Multi-class classification (cross-entropy).
1:33
An example for multi-class case.
1:46
Some ML algorithms have their own losses.
1:58
Future topics.
2:01
Subscribe to us!
Playlist
Uploads from AI For Beginners ยท AI For Beginners ยท 15 of 32
1
2
3
4
5
6
7
8
9
10
11
12
13
14
โถ
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Artificial Intelligence Explained In Simple Words | What Is AI? | Explained On A Real World Example!
AI For Beginners
AI vs. ML vs. DL vs. DS - Difference Explained | On Real World Examples | AI For Beginners
AI For Beginners
Types Of Machine Learning Algorithms | Explained On Real World Examples | ML For Beginners
AI For Beginners
Best AI Music Generator | Music Generation Tool for FREE | MusicGen developed by Meta AI
AI For Beginners
The Ultimate Guide To Supervised Learning | Explained On Binary Classification Example | Part 1
AI For Beginners
The Ultimate Guide To Supervised Learning | Classification And Regression | Part 2
AI For Beginners
Linear Regression Explained | A Beginner's Guide To Regression | The Basics You Need to Know!
AI For Beginners
Assumptions Of Linear Regression | What To Do If The Assumptions Do Not Hold? | Part 1
AI For Beginners
Checking The Assumptions Of Linear Regression | Statistical And Visual Methods | Part 2
AI For Beginners
The Purpose of Train-Test Split in Machine Learning | How to Correctly Split Data?
AI For Beginners
The Role of Validation Sets in Model Training | Train-Test-Validation Splits | Clearly explained!
AI For Beginners
Overfitting and Underfitting | Bias and Variance Tradeoff in Machine Learning | Clearly Explained!
AI For Beginners
Gradient Descent Explained | How Do ML and DL Models Learn? | Simple Explanation!
AI For Beginners
Main Types of Gradient Descent | Batch, Stochastic and Mini-Batch Explained! | Which One to Choose?
AI For Beginners
The Role of Loss Functions | Most Common Loss Functions in Machine Learning | Explained!
AI For Beginners
How to Evaluate Your ML Models Effectively? | Evaluation Metrics in Machine Learning!
AI For Beginners
8 Best Tips For Cleaning Your Data | Data Cleaning | Machine Learning, Data Preparation.
AI For Beginners
Numerical vs. Categorical Data | Represent Your Dataset Correctly!
AI For Beginners
3 Main Types of Missing Data | Do THIS Before Handling Missing Values!
AI For Beginners
7 PROVEN Strategies To Become An AI Engineer (2025 Updated)
AI For Beginners
Easiest Guide to K-Fold Cross Validation | Explained in 2 Minutes!
AI For Beginners
Normalization and Standardization | Why to Scale the Features? | ML Basics
AI For Beginners
The Ultimate Guide to Hyperparameter Tuning | Grid Search vs. Randomized Search
AI For Beginners
How is Artificial Intelligence different from Traditional Programming?
AI For Beginners
All Machine Learning Models Clearly Explained!
AI For Beginners
6 Mistakes to Avoid When Learning Machine Learning in 2025
AI For Beginners
Best Practices for Effective Data Visualization In Machine Learning!
AI For Beginners
Central Limit Theorem Intuition Explained Like You're 5!
AI For Beginners
Which Door Would You Choose? | Monty Hall Problem Explained!
AI For Beginners
All Machine Learning Concepts Explained in 18 Minutes!
AI For Beginners
Whatโs the Probability That Two Randomly Drawn Chords in a Circle Intersect?
AI For Beginners
Causation vs Correlation | The Most Confused Concept in Data Science
AI For Beginners
DeepCamp AI