Python Machine Learning for Healthcare - Predictive Modeling and Disease Detection
Created by Team Mammoth
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69 lectures
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Skill level
All levels
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Sections
13
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Lectures
69
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Instructor
Team Mammoth
What's inside
This course includes.
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13
Sections
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Certificate of completion
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Mobile and desktop access
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AI learning assistance
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Course content
Curriculum & lectures.
+ Regression Fundamentals - Theory Behind the Code 4 lectures
01 Regression Introduction
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02 What Is Regression
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03 What Is Linear Regression
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+ Build a K Nearest neighbors regression model to predict diabetes 5 lectures
00 Project Preview
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01 What Is K Nearest Neighbours
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01 Load And Analyze Data
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02 Build A K Nearest Neighbors Regression Model To Predict Diabetes
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+ Build Regression Machine Learning Models to Detect Diabetes 5 lectures
03A What Is The Random Forest Classifier Model
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03B Build More Regression Models And Find The Best One
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04 Select Top Features Via Variance Threshold
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05 Visualize Linear Regression With Matplotlib Pyplot
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+ Data analysis and transformation on blood cell data 7 lectures
00 Project Preview
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01 Load And Analyze Blood Cell Data
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02 Clean Data With Missing Values
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03 Process Data For Machine Learning
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04A What Is Principal Component Analysis
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04B Reduce Data Dimensionality With Principal Component Analysis
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+ Cluster blood cells based on fluorescent intensities 5 lectures
05A What Is Unsupervised Learning
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05B What Is K Means Clustering
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05C Build A Kmeans Clustering Model
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06 Visualize Clusters Found Via Kmeans
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+ Preprocess a malignant vs benign cancer mass dataset 4 lectures
00 Project Preview
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01 Load And Analyze Cancer Dataset
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02 Preprocess Cancer Data For Machine Learning
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+ Build an SVM model to classify malignant vs benign cancer mass 7 lectures
03A Why Do We Need Svm
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03B How Does Svm Work
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03C Svm On Non-Linear Data
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03D What Are Svm Kernels
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03E What Is The Precision-Recall Score
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03F Build An Svm Model To Classify Malignant Vs Benign Mass
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+ Build a logistic regression model to classify malignant vs benign cancer mass 3 lectures
04A What Is Logistic Regression
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04B Build A Logistic Regression Model
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+ Improve model accuracy with tuning methods 9 lectures
01A What Is Cross Validation
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01B Find Model Error With Cross Validation
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02A What Is Grid Search Cross Validation
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02B Find Optimal Hyperparameters With Grid Search
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03A What Is Nested Cross Validation
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03B Find Best Model Parameters With Nested Cross Validation
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04A What Is The Decision Tree Model
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04B Compare Models With Nested Cross Validation
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+ Prepare heart disease data for machine learning 4 lectures
01 Load Data Via Data File
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02 Clean And Preprocess Heart Disease Data For Machine Learning
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03 Process Heart Disease Data For Machine Learning
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+ Predict heart disease with machine learning 6 lectures
04A What Is Stochastic Gradient Descent
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04B Build A Linear Classifier With Stochastic Gradient Descent
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05A What Is Ada Boost
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05B Build An Ada Boost Classifier
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06 Build A K Nearest Neighbors Machine Learning Model
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+ Deep learning and neural networks introduction 3 lectures
01 What Is Deep Learning
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02 What Is A Neural Network
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+ Build a neural network to find malaria in cells 7 lectures
00 Project Preview
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01 Load Data Via Tensorflow
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02 Visualize Malaria Cell Images
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03 Extract A Subset Of Samples
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04 Build A Neural Network
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05 Train And Evaluate Model Accuracy
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Instructors
Taught by people who ship.
Team Mammoth
Instructor
Produced by a team of Mammoth Club industry experts. Over 14 years, Mammoth Club has built a global student community in 190+ countries with 9+ million courses sold, releasing over 1,000+ courses and 5,000+ hours of video content.
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