🔅 Machine Learning and AI Foundations: Causal Inference and Modeling
🌐 Author: Keith McCormick
🔰 Level: Advanced
⏰ Duration: 2h 51m
📗 Topics: Causal Inference, Machine Learning, Artificial Intelligence
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🌀 Learn about the modeling techniques and experimental designs that allow you to establish causal inference, and how to use them.
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Machine_Learning_and_AI_Foundations_Causal_Inference_and_Modeling.zip
459.4 MB
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🔅 Building a Video Transcriber with Node.js and Google AI Speech-To-Text API
🌐 Author: Fikayo Adepoju
🔰 Level: Intermediate
⏰ Duration: 1h 9m
📗 Topics: Machine Trannoscription, Artificial Intelligence, Node.js
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🌀 Learn how to transcribe audio from video by integrating Node.js applications with the Google AI Speech-to-Text API.
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Building_a_Video_Transcriber_with_Node_js_and_Google_AI_Speech_To.zip
139.5 MB
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1️⃣ Linear Regression: Think of it as drawing a straight line through data points to predict future outcomes.
2️⃣ Logistic Regression: Like a yes/no machine - it predicts the likelihood of something happening or not.
3️⃣ Decision Trees: Imagine making decisions by answering yes/no questions, leading to a conclusion.
4️⃣ Random Forest: It's like a group of decision trees working together, making more accurate predictions.
5️⃣ Support Vector Machines (SVM): Visualize drawing lines to separate different types of things, like cats and dogs.
6️⃣ K-Nearest Neighbors (KNN): Friends sticking together - if most of your friends like something, chances are you'll like it too!
7️⃣ Neural Networks: Inspired by the brain, they learn patterns from examples - perfect for recognizing faces or understanding speech.
8️⃣ K-Means Clustering: Imagine sorting your socks by color without knowing how many colors there are - it groups similar things.
9️⃣ Principal Component Analysis (PCA): Simplifies complex data by focusing on what's important, like summarizing a long story with just a few key points.
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This course is designed to introduce beginner-level programmers to the fundamentals of writing clean, efficient code with the help of AI-based programming assistants. It covers best practices in coding, prompt engineering for AI tools, and techniques to accelerate the development process.
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