Machine Learning A-Z™: Hands-On Python & R In Data Science
by Kirill Eremenko and Hadelin de Ponteves on Udemy
(Image: Udemy)
Actually a couple of new jobs and task at work and obviously major curiosity have led me to have a dive into Machine Learning. Guess what, I absolutely love it. It’s fantastic to get your head around the theory, but also try out some simple examples of applied ML – even if it is just to understand when people talk about it. Actually applying it to own real world problems is of course a different story, but this is a first step for me. It all boils down to ask the right question and to understand what the data might be able to tell you, rather then using Machine Learning for the sake of it.
I highly recommend the course, join me if you’d like!
This is the table of content as described on Udemy:
Part 1 – Data Preprocessing
Part 2 – Regression:
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- SVR
- Decision Tree Regression
- Random Forest Regression
Part 3 – Classification:
- Logistic Regression
- K-NN
- SVM
- Kernel SVM
- Naive Bayes
- Decision Tree Classification
- Random Forest Classification
Part 4 – Clustering:
- K-Means
- Hierarchical Clustering
Part 5 – Association Rule Learning:
- Apriori
- Eclat
Part 6 – Reinforcement Learning:
- Upper Confidence Bound
- Thompson Sampling
Part 7 – Natural Language Processing: Bag-of-words model and algorithms for NLP
Part 8 – Deep Learning:
- Artificial Neural Networks
- Convolutional Neural Networks
Part 9 – Dimensionality Reduction:
- PCA
- LDA
- Kernel PCA
Part 10 – Model Selection & Boosting:
- k-fold Cross Validation
- Parameter Tuning
- Grid Search
- XGBoost
I wanted to post this in the off chance you’d be able to assist. I tried your tutorial for installing FLTK and when I hit F5 after adding all the dependencies, etc., I get the error “cannot open file ‘wsock32.lib'”. I haven’t seen anyone else have this error so I was curious if you may have any insight. Thanks for the great, easy-to-follow tutorial! The best I’ve found.