Model Evaluation Courses

Introduction to Machine Learning

  4.46 76.4K+ learners 1 hr

Skills: Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Linear Regression, Classification, Recommender System, Kaggle, Hackathon, ML on Cloud, Data Science, Model Training, Machine Learning Platforms, Data-Driven Intelligence

Python for Machine Learning

  4.51 466.2K+ learners 1.5 hrs

Skills: NumPy Arrays, NumPy Operations, NumPy Math, Saving & Loading NumPy, Pandas Series, Pandas DataFrame, Pandas Functions (Mean, Median, Max, Min), Data Manipulation, Supervised Learning, Unsupervised Learning, Machine Learning with Python

Supervised Machine Learning with Tree Based Models

  4.56 9.8K+ learners 2 hrs

Skills: Scikit Learn Library, Decision Tree, Random Forest, Demonstration for Algorithms

Supervised Machine Learning with Logistic Regression and Naïve Bayes

  4.43 21.7K+ learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

KNN Algorithm

  4.41 3K+ learners 0.5 hr

Skills: KNN, KNN Demo

Unsupervised Machine Learning with K-means

  4.42 11.5K+ learners 1.5 hrs

Skills: Unsupervised Learning,Clustering, k-means Clustering

Hierarchical Clustering

  4.52 2.1K+ learners 1 hr

Skills: Introduction to Hierarchical Clustering, Agglomerative Hierarchical Clustering, Euclidean Distance, Manhattan Distance, Minkowski Distance, Jaccard Index, Cosine Similarity, Optimal Number of Clusters

Feature Engineering

  4.58 3.2K+ learners 1.5 hrs

Skills: Process of feature engineering, Feature engineering techniques, Correlation matrix, Model performance analysis, Feature engineering demo using a real-life dataset

Feature Engineering Importance

  4.54 1.6K+ learners 1 hr

Skills: Feature Engineering, Feature Selection

Machine Learning Modelling

  4.62 4.8K+ learners 2.5 hrs

Skills: Linear Regression, Logistic Regression, Naïve Bayes

k-fold Cross Validation

  4.61 1.8K+ learners 1 hr

Skills: Introduction to Cross Validation, Process of Cross Validation, Types of Cross Validation

Bias Variance Tradeoff

  4.59 1.2K+ learners 0.5 hr

Skills: Bias, Variance, Trade-off, How to avoid overfitting and underfitting?