Intermediate Outlier Detection
Detecting outlier data points are powerful machine learning techniques. This course covers how techniques like Local Outlier Factor and Isolation Fore…
Course Category: Data Science (Python)
Introduction to Outlier Detection
Detecting outlier data points are powerful machine learning techniques. This class will build upon foundational machine learning techniques to discove…
Feature Engineering
This course helps students to identify the most impactful features for your model. It will build upon foundational machine learning techniques to h…
Advanced Clustering in Python
In this course, learners will prepare data for, implement, and optimize three advanced clustering models in Python while comparing their different …
Intermediate Clustering in Python
In this course, learners will encounter more sophisticated methods for generating clusters within unlabeled data using Python. The first method, hiera…
Introduction to Clustering in Python
Clustering is a machine learning technique that can be used to group unlabeled data based on shared features. In this course, learners will identify u…
Sentiment Analysis in NLP
This course covers the intermediate concepts of natural language processing like sentiment analysis. By the end of this course students will be able t…
Word Embeddings in NLP
This course covers the intermediate concepts of natural language processing like creating word embeddings, feature engineering and word embeddings for…
Clustering in NLP
This course covers the clustering concepts of natural language processing, equipping learners with the ability to cluster text data into groups and…
Topic Modeling in NLP
This course intermediate concepts in natural language processing, equipping learners with the ability to clean and process large amounts of text data,…
