Learn basics concepts of ML, deep learning, and AI tools with practical examples and beginner-friendly explanitions.
Sub Category
- Data Science
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Objectives
- Understand the core concept of machine learning and how it powers modern AI systems.
- Get introduced to neural networks — the building blocks of modern AI, and learn how backpropagation works.
- Dive into deep learning and how it powers things like image recognition and voice assistants.
- Learn the difference between supervised, unsupervised, and reinforcement learning.
- Build models for classification and regression to make predictions from data.
- Explore clustering and density estimation for discovering patterns in unlabeled data.
- Master data preprocessing techniques like handling missing values, normalization, and feature engineering.
- Evaluate models using ROC curves, AUC, and other performance metrics.
- Understand how probability helps machines make smarter guesses, including Bayes classifiers and logistic regression.
- Apply linear models and optimize them using gradient descent.
- Learn about generative models such as GANs and variational autoencoders (VAEs).
- Understand how machines deal with sequences, like predicting the next word in a sentence.
- Implement ensemble methods like bagging, boosting, and random forests.
- Work with sequence models including RNNs and LSTMs for time-series and text.
- Build embedding models for recommender systems and graph-based learning.
- Understand reinforcement learning concepts like policy gradients and Q-learning.
- Reflect on the social and ethical impact of machine learning in real-world applications.
Pre Requisites
- Familiarity with high school-level mathematics (algebra, probability, and statistics).
- Curiosity and motivation to learn machine learning concepts deeply.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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