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Python Machine Learning for Healthcare - Predictive Modeling and Disease Detection
Regression Fundamentals - Theory Behind the Code
01 Regression Introduction (8:58)
02 What Is Regression (19:55)
03 What Is Linear Regression (5:03)
Source files
Build a K Nearest neighbors regression model to predict diabetes
01 Project Preview (2:14)
02 Load And Analyze Data (8:25)
03 What Is K Nearest Neighbours (8:07)
04 Build A K Nearest Neighbors Regression Model To Predict Diabetes (10:24)
Source files
Build Regression Machine Learning Models to Detect Diabetes
01 What Is The Random Forest Classifier Model (5:42)
02 Build More Regression Models And Find The Best One (4:08)
03 Select Top Features Via Variance Threshold (12:42)
04 Visualize Linear Regression With Matplotlib Pyplot (6:14)
Source Files
Data analysis and transformation on blood cell data
00 Project Preview (2:56)
01 Load And Analyze Blood Cell Data (10:39)
02 Clean Data With Missing Values (12:28)
03 Process Data For Machine Learning (8:53)
04 What Is Principal Component Analysis (7:27)
05 Reduce Data Dimensionality With Principal Component Analysis (4:55)
Source Files
Cluster blood cells based on fluorescent intensities
00 What Is Unsupervised Learning (8:17)
01 What Is K Means Clustering (11:58)
02 Build A Kmeans Clustering Model (12:23)
03 Visualize Clusters Found Via Kmeans (8:09)
Source files
Preprocess a malignant vs benign cancer mass dataset
01 Project Preview (2:22)
02 Load And Analyze Cancer Dataset (5:46)
03 Preprocess Cancer Data For Machine Learning (5:24)
Source files
Build an SVM model to classify malignant vs benign cancer mass
01 Why Do We Need SVM (7:15)
02 How Does SVM Work (6:28)
03 SVM On Non-Linear Data (4:48)
04 What Are SVM Kernels (4:44)
05 What Is The Precision-Recall Score (4:42)
06 Build An SVM Model To Classify Malignant Vs Benign Mass (4:08)
Source Files
Build a logistic regression model to classify malignant vs benign cancer mass
01 What Is Logistic Regression (4:32)
02 Build A Logistic Regression Model (3:44)
Source files
Improve model accuracy with tuning methods
01 What Is Cross Validation (8:25)
02 Find Model Error With Cross Validation (3:46)
03 What Is Grid Search Cross Validation (5:47)
04 Find Optimal Hyperparameters With Grid Search (9:37)
05 What Is Nested Cross Validation (14:29)
06 Find Best Model Parameters With Nested Cross Validation (4:43)
07 What Is The Decision Tree Model (10:51)
08 Compare Models With Nested Cross Validation (4:00)
Source Files
Prepare heart disease data for machine learning
01 Load Data Via Data File (11:11)
02 Clean And Preprocess Heart Disease Data For Machine Learning (11:44)
03 Process Heart Disease Data For Machine Learning (8:39)
Source Files
Predict heart disease with machine learning
01 What Is Stochastic Gradient Descent (11:28)
02 Build A Linear Classifier With Stochastic Gradient Descent (8:05)
03 What Is ADA Boost (5:48)
04 Build An ADA Boost Classifier (7:17)
05 Build a K Nearest Neighbors Machine Learning Model (8:03)
Source Files
Deep learning and neural networks introduction
01 What Is Deep Learning (7:42)
02 What Is A Neural Network (8:47)
Source files
Build a neural network to find malaria in cells
01 Project Preview (1:15)
02 Load Data Via Tensorflow (4:06)
03 Visualize Malaria Cell Images (8:49)
04 Extract A Subset Of Samples (8:03)
05 Build A Neural Network (5:41)
06 Train And Evaluate Model Accuracy (9:23)
Source Files
06 Find Best Model Parameters With Nested Cross Validation
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