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The Complete Healthcare Artificial Intelligence Course 2022

via Udemy


Creating powerful AI model for Real-World Healthcare applications with Data Science, Machine Learning and Deep Learning

What you'll learn:
  • Pandas.
  • Matplotlib.
  • Sigmoid activation function.
  • Tanh activation function.
  • ReLU activation function.
  • Leaky Relu activation function.
  • Exponential Linear Unit activation function.
  • Swish activation function.
  • Markov models.
  • Support Vector Machines
  • Other common classifiers
  • Import data from the UCI repository.
  • Convert text input to numerical data.
  • Build and train classification algorithms.
  • Compare and contrast classification machine learning.
  • Building the AI.
  • Machine learning and deep learning model based on the given data with high accuracy.
  • RF with Response Coding.
  • Maximum voting Classifier.
  • Stacking model.
  • Random Forest Classifier.
  • One-hot Encoding.
  • NLP (Natural Language Processing)
  • NLTK (Natural Language Toolkit)
  • Logistic Regression.
  • Naive Bayes
  • Response Encoding
  • Linear Support Vector Machines
  • Geolocation Features.
  • Handling Missing Data And Anomalies in Python.
  • Data standardization.
  • Temporal Features.
  • Seaborn
  • Deep Learning.
  • Keras.
  • Google Colab .
  • Anaconda.
  • Jupiter Notebook.

Interested in the field of Machine Learning, Deep Learning and Artificial Intelligence? Then this course is for you!

This course has been designed by a software engineer. I hope with my experience and knowledge I did gain throughout years, I can share my knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

I will walk you step-by-step into the Machine Learning, Artificial Intelligence and Deep Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Machine Learning, Deep Learning and Artificial Intelligence . Throughout the brand new version of the course we cover tons of tools and technologies including:

  • Deep Learning.

  • Google Colab

  • Anaconda

  • Jupiter Notebook

  • Artificial Intelligent In Healthcare.

  • Artificial Neural Network.

  • Neuron.

  • Activation Function.

  • Keras.

  • Pandas.

  • Seaborn.

  • Feature scaling.

  • Matplotlib.

  • Generating a DNA Sequence.

  • Data Pre-processing.

  • Sigmoid Function.

  • Tanh Function.

  • ReLU Function.

  • Leaky Relu Function.

  • Exponential Linear Unit Function.

  • Swish function.

  • Markov Models.

  • K-Nearest Neighbors Algorithms (KNN).

  • Support Vector Machines (SVM).

  • Importing library and data.

  • Deep feedforward networks.

  • Analysing Data.

  • Exploratory Analysis.

  • Handling Missing Data And Anomalies in Python.

  • Data standardization.

  • Temporal Features.

  • Geolocation Features.

  • Data Scaling.

  • Data Visualization.

  • Visualizing Geolocation Data.

  • Understanding Machine Learning Algorithm.

  • Splitting Data into Training Set and Test Set.

  • Training Neural Network.

  • Model building.

  • Analysing Results.

  • Model compilation.

  • A Comparison Of Categorical And Binary Problem.

  • Make a Prediction.

  • Testing Accuracy.

  • Confusion Matrix.

  • ROC Curve.

  • One-hot Encoding.

  • NLP (Natural Language Processing).

  • NLTK (Natural Language Toolkit).

  • Logistic Regression.

  • Naive Bayes.

  • Response Encoding.

  • Linear Support Vector Machines.

  • RF with Response Coding.

  • Random Forest Classifier.

  • Stacking model.

  • Maximum voting Classifier.

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are five big projects on healthcare problems and one small project to practice. These projects are listed below:

  • Predicting Taxi Fares in New York City

  • DNA Classification Project.

  • Heart Disease Classification Project.

  • Diagnosing Coronary Artery Disease Project.

  • Breast Cancer Detection Project.

  • Predicting Diabetes with Multilayer Perceptrons Project.

  • Iris Flower.

  • Medical Treatment Project.

Taught by

Hoang Quy La


4.5 rating at Udemy based on 63 ratings

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