What is machine learning?
How Machine Learning Works in Practice
The Three Main Types of Machine Learning
Supervised Learning Fundamentals
Linear Regression with Classic Programming
Linear Regression with Machine Learning
Full Batch, Mini Batch and Stochastic Gradient Descent
The Artificial Neuron and Neural Networks
Linear Regression with a Single Neuron
Linear Regression with the Algebraic Method (Part 1)
Linear Regression with the Algebraic Method (Part 2)
One Dimensional Linear Regression (Algebraic Method)
Linear Regression with Neural Networks
Building a Simple Neural Network for Regression
Linear Regression with Two Outputs (Part 1)
Linear Regression with Two Outputs (Part 2)
A Deep Neural Network for Digit Classification
Defining the Classification Network in Code
Training the Digit Recognition Model
Testing and Evaluating the Model
From Pixels to Predictions with Convolutional Neural Networks
K Means Clustering: Theory and Intuition
Implementing K Means Clustering in Python
DBSCAN Clustering: Theory and Intuition
Implementing DBSCAN Clustering in Python
Dimensionality Reduction: Key Concepts
Dimensionality Reduction in Python (PCA)
Introduction to Reinforcement Learning
Solving CartPole with PPO (Stable Baselines3)
Lunar Lander with PPO: From Setup to Landing
Building a Custom Reinforcement Learning Environment
Conclusion and Where to Go Next
I was looking for a hands-on course, and this one met my expectations. The instructor seemed knowledgeable and guided well, from the artificial neuron to "Building a Simple Neural Network for Regression." I appreciated the opportunities to apply w...
Leggi di PiùI was looking for a hands-on course, and this one met my expectations. The instructor seemed knowledgeable and guided well, from the artificial neuron to "Building a Simple Neural Network for Regression." I appreciated the opportunities to apply what I learned, because each concept (e.g., regression with two outputs) translates into an implementation step.
Leggi MenoI enjoyed the instructor's presentation because it was engaging without becoming distracting. I gained valuable insights into the training pipeline, thanks to the lessons on training, testing, and evaluating the digit classification model. Further...
Leggi di PiùI enjoyed the instructor's presentation because it was engaging without becoming distracting. I gained valuable insights into the training pipeline, thanks to the lessons on training, testing, and evaluating the digit classification model. Furthermore, there were plenty of opportunities to apply what I learned by writing code to define the network and run tests.
Leggi MenoIl corso ha rispettato le mie aspettative perché parte dalle basi (“What is machine learning?”) e arriva a implementazioni concrete. L’insegnante è apparso preparato e si vede quando guida dalla teoria del neurone fino alla regressione con una sin...
Leggi di PiùIl corso ha rispettato le mie aspettative perché parte dalle basi (“What is machine learning?”) e arriva a implementazioni concrete. L’insegnante è apparso preparato e si vede quando guida dalla teoria del neurone fino alla regressione con una singola unità. Le spiegazioni sono state chiare anche nella parte di training e valutazione del modello per il riconoscimento di cifre.
Leggi Meno