If you’re a machine learning specialist looking to make the transaction into the real-world AI applications.

This comprehensive course will be your guide to learning how to scale-up your machine learning model to the optimal state possible, you 'll be learning everything you need to move you machine learning model to the next stage.

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

You'll learn the machine learning, AI, and data mining techniques real employers are looking for, including:

Handling Missing Values

Label Encoder

One-Hot Encoder

Normalization

Standardization

Binarization

Principal Analysis Component (PCA)

Manual Feature Engineering

Automatic Feature Engineering

Feature Selection

Model Evaluation

Confusion Matrix

Precision and Recall

F1-score and Fbeta-score

Area Under Curve (AUC)

Overfitting vs Underfitting

Cross-Validation

Analyzing Learning Curves

Hyperparameters Tuning