| 1. Clustering algorithms.mp4 | 17 MB | ||
| 1. Definition and history of artificial intelligence.mp4 | 18.7 MB | ||
| 1. Introduction to machine learning.mp4 | 14.5 MB | ||
| 1. Linear regression and logistic regression.mp4 | 13.8 MB | ||
| 1. Markov decision processes.mp4 | 17 MB | ||
| 1. Overview of statistics and probability.mp4 | 25 MB | ||
| 1. Recap of key concepts and takeaways.mp4 | 13 MB | ||
| 1. Sources of data and methods of collecting data.mp4 | 23.4 MB | ||
| 1. The impact of AI on society and ethics.mp4 | 28.3 MB | ||
| 1. Univariate and multivariate analysis.mp4 | 22.8 MB | ||
| 1. What is data science and why is it important.mp4 | 14.1 MB | ||
| 2. Bias in AI and its implications.mp4 | 15.7 MB | ||
| 2. Data visualization techniques.mp4 | 18.3 MB | ||
| 2. Decision trees and random forests.mp4 | 14.4 MB | ||
| 2. Different types of machine learning algorithms.mp4 | 24.4 MB | ||
| 2. Dimensionality reduction.mp4 | 19.5 MB | ||
| 2. Introduction to regression and classification models.mp4 | 9.1 MB | ||
| 2. Opportunities and challenges in data science, machine learning, and AI.mp4 | 28.2 MB | ||
| 2. Q-learning.mp4 | 11.4 MB | ||
| 2. The process of data science and its different stages.mp4 | 27.3 MB | ||
| 2. Types of artificial intelligence and their applications.mp4 | 25.7 MB | ||
| 2. Understanding and cleaning data.mp4 | 21.8 MB | ||
| 3. Anomaly detection.mp4 | 18.1 MB | ||
| 3. Dealing with missing and duplicate values.mp4 | 15.5 MB | ||
| 3. Different fields that use data science and examples of real-world applications.mp4 | 26.4 MB | ||
| 3. Fairness and accountability in AI.mp4 | 14 MB | ||
| 3. Identifying relationships and patterns in data.mp4 | 22.2 MB | ||
| 3. Natural language processing and computer vision.mp4 | 11 MB | ||
| 3. Overfitting and regularization.mp4 | 9.5 MB | ||
| 3. Overfitting and underfitting.mp4 | 16.2 MB | ||
| 3. Policy gradient methods.mp4 | 19.3 MB | ||
| 3. Suggestions for further learning and resources.mp4 | 23.2 MB | ||
| 3. Support vector machines.mp4 | 9.8 MB | ||
| 4. Best practices for avoiding bias in AI models.mp4 | 17.9 MB | ||
| 4. Feature engineering and selection.mp4 | 20.7 MB | ||
| 4. Feature scaling and normalization.mp4 | 9.9 MB | ||
| 4. Model evaluation and selection.mp4 | 18.5 MB | ||
| 4. Neural networks and deep learning.mp4 | 14 MB | ||
| 4. Overview of deep learning and its applications.mp4 | 17.6 MB | ||
| 4. Overview of the tools and techniques used in data science.mp4 | 25.1 MB | ||
| 4. Quiz.html | 204.8 B | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 43 total files | |||
Mastering Data Science, Machine Learning, and AI
https://DevCourseWeb.com
Published 2/2023
Created by Thomas Keyt
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 40 Lectures ( 1h 48m ) | Size: 732 MB
From Beginner to Expert
What you'll learn
Introduction to Data Science
Data Collection and Preprocessing
Exploratory Data Analysis
Statistical Modeling
Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Artificial Intelligence
Ethics and Bias in AI
Conclusion
Requirements
No Programming experience needed, you will learn what you need to know
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