Udemy - Machine Learning Prediction Model from Scratch for Everyone

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Udemy - Machine Learning Prediction Model from Scratch for Everyone (Size: 549.6 MB)
  1. Congratulations and Future Direction.mp4 21.7 MB
  1. Designing Form for Data Collection.mp4 60.1 MB
  1. Introduction to Google Collab and Python.mp4 41.6 MB
  1. Overview of the course and Resource Materials.mp4 39.6 MB
  1.1 dataset1.1.csv 1.9 KB
  1.2 depression_prediction_code.ipynb 102.3 KB
  2. Data Preprocessing.mp4 60.1 MB
  2. Importing Dataset and Preparation at Google Colab.mp4 56.3 MB
  2. Introduction.mp4 19.3 MB
  2. QUIZ.html 204.8 B
  3. Data Analysis with Python Libraries.mp4 34.4 MB
  3. Data Preprocessing and preparation.mp4 49 MB
  3. Types of Machine Learning.mp4 26.5 MB
  4. Prediction Model Naive Bayes and Random Forest.mp4 37.3 MB
  5. Prediction Model SVM with Confusion Matrix.mp4 70.4 MB
  6. Testing Model with Random Data.mp4 33.3 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 18 total files

Description


Machine Learning Prediction Model from Scratch for Everyone

https://DevCourseWeb.com

Published 9/2023
Created by Mehedi Hasan Abid
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 13 Lectures ( 56m ) | Size: 550 MB

From Scratch (Data Collection to Apply Algorithms) learn to Develop Naïve Bayes | Random Forest | SVM and Much More

What you'll learn
Machine learning fundamentals: supervised, unsupervised, reinforcement learning, and practical applications.
Master data preprocessing: handle missing data, scale features, and transform datasets for ML.
Explore various ML algorithms, understanding when and how to use them effectively
Evaluate models with metrics like accuracy, precision, recall, and understand the importance of cross-validation.
Develop coding skills from scratch, understanding the inner workings of ML models.
Engage in hands-on projects, building a portfolio nstrating practical ML expertise.
And Finally publish Research Articles or do project with own understanding

Requirements
No prerequisites required. You will learn everything you need to know.

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