Half 3 of the five-part sequence: Motivation and Precision
Take a look at Part 1 and Part 2 as nicely, there’s precious data in every writing.
Introduction
Wanting again, the interval after I started to grapple with the fabric I’m about to share, was maybe probably the most difficult chapter of my journey. The extent of effort required skyrocketed; my normal three hours of day by day research, ballooned to 5 or 6 hours. Thoughts you, this was after clocking out from my day job. It was an arduous job, however failure was not an possibility — cliché or not.
The next content material will cowl the areas of:
- Linear Fashions — (
Linear and Logistic Regression) - Assist Vector Machines — (
Linear SVM and Kernel SVM) - Resolution Timber and Ensembles — (
Resolution Timber, Random Forest, and Gradient Boosting) - Neural Networks — (
FNN, CNN and RNN) - Clustering — (
Okay-Means, Hierarchical Clustering, and DBSCAN) - Dimensionality Discount — (
PCA, t-SNE, and LDA) - Bayesian Fashions — (
Naive Bayes and Bayesian Networks) - Utilized Modeling — (
Outline ML issues, Mannequin analysis, and Establishing metrics)
