Udemy – Python for Machine Learning and Deep Learning in One Semester 2023-8 – Downloadly

Description

Introduction to Python for Machine Learning and Deep Learning in a semester course

  1. Course introduction
  2. An introduction to machine learning and deep learning
  3. Introduction to Google Colab
  4. Python crash course
  5. Data preprocessing

supervised machine learning

  1. Regression analysis
  2. logistic regression
  3. K-Nearest Neighbor (KNN)
  4. Bayes theorem and simple Bayes classifier
  5. Support Vector Machine (SVM)
  6. Decision trees
  7. random forest
  8. Reinforcement methods in machine learning
  9. An introduction to neural networks and deep learning
  10. Activation functions
  11. Loss functions
  12. let go again
  13. Neural networks for regression analysis
  14. Neural networks for classification
  15. Deletion regularization and batch normalization
  16. Convolutional Neural Network (CNN)
  17. Recurrent neural network (RNN)
  18. Auto encoder
  19. Generative Adversarial Network (GAN)

Unsupervised machine learning

  1. K-Means Clustering
  2. hierarchical clustering
  3. Density-based spatial clustering of noisy applications (DBSCAN)
  4. Gaussian mixture model (GMM) clustering.
  5. Principal Component Analysis (PCA)

What you will learn in the Python for Machine Learning and Deep Learning in One Semester course

  • Theory, mathematics and implementation of machine learning and deep learning algorithms.
  • Regression analysis.
  • Classification models used in classical machine learning such as logistic regression, ANN, support vector machines, decision trees, random forest, and reinforcement learning methods.
  • Build artificial neural networks and use them for regression and classification problems.
  • Using a GPU with deep learning models
  • Convolutional neural networks
  • Transfer learning
  • Recurrent neural networks
  • Prediction and classification of time series
  • Auto encoder
  • Hostile productive networks
  • Python from scratch
  • Numpy, Matplotlib, Seaborn, Pandas, Pytorch, Scikit-Learn and other Python libraries.
  • More than 80 projects were solved using machine learning and deep learning models.

This course is suitable for people who

  • Students of the courses “Machine Learning” and “Deep Learning”.
  • Beginners who want to learn machine learning and deep learning from scratch
  • Artificial intelligence researcher
  • Students and researchers who want to develop Python programming skills to solve machine learning and deep learning tasks.
  • Those who know MATLAB and other programming languages ​​and want to switch to Python for machine learning and deep learning.

Details about the course “Python for Machine Learning and Deep Learning in One Semester”.

  • Editor: Udemy
  • Lecturer: Zeeshan Ahmed
  • Training level: beginner to advanced
  • Training duration: 46 hours and 45 minutes
  • Number of courses: 305

Course topics “Python for Machine Learning and Deep Learning” in one semester

Python for Machine Learning and Deep Learning in One Semester

Prerequisites for Python for Machine Learning and Deep Learning in a Semester Course

  • Some programming knowledge is desirable but not necessary
  • Gmail account (for Google Colab)

Course pictures

Python for Machine Learning and Deep Learning in One Semester

Sample video of the course

installation Guide

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Quality: 720p

Download link

Download Part 1 – 3 GB

Download Part 2 – 3 GB

Download Part 3 – 3 GB

Download Part 4 – 3 GB

Download Part 5 – 3 GB

Download Part 6 – 0.3 GB

File(s) password: www.downloadly.ir

File size

15.3GB

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