Python Foundation


Machine Learning

Categories: Python with ML
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About Course

Machine Learning coaching from Python Foundation can assist you to become knowledgeable in advanced Python, because it is totally supported python. we tend to ar having the trainers having over five years of expertise in Machine Learning victimisation Python. they’re the trade skilled, who knows, a way to train students for the trade so they’re going to get an honest job instantly once obtaining the coaching type the Python Foundation.
We will assist you to figure on the period and also the project-based coaching in Python Foundation. we tend to conjointly offer employment-based coaching with a job placement too.


Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.



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What Will You Learn?

  • Automation of Everything. Machine Learning is chargeable for cutting the work and time.
  • Wide Range of Applications.
  • Scope of Improvement.
  • Efficient Handling of knowledge.
  • Best for Education and on-line looking.
  • Possibility of High Error.
  • Algorithm choice.
  • Data Acquisition.

Course Content

What is ML?

  • Overview of ML
  • Different Types of ML : Supervised, Unsupervised, Reinforcement, Self-supervised

Supervised Learning – Regression

Types of Regression

Regularization in Regression

Supervised Learning – Classification

Classification Model – Logistic Regression

Classification Model – Decision Tree Classification

Classification Model – Random Forest Classification

Classification Model – KNN Classification

Classification Model – SVM Classification

Classification Model – Naive Bayes Classification

Bagging vs Boosting

Boosting algorithms – AdaBoost

Boosting algorithms – Gradient Boost

Boosting algorithms – XGBoost

Hyperparameter Tuning

Unsupervised Learning – Clustering

Unsupervised Learning – K-Means Clustering

Unsupervised Learning – Agglomerative Clustering

Unsupervised Learning – DBSCAN Clustering

Unsupervised Learning – Dimensionality Reduction

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