Arguably, the best Linear Algebra course out there for Machine Learning! Taught by MIT's Professor Gilbert Strang. And it's FREE! Build a strong foundation in mathematics for machine learning: https://
youtube.com/playlist?list=
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@sumanth_077
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Free MIT Linear Algebra Course for Machine Learning Foundations
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Python, Machine Learning, MLOps, CV/NLP, LLMs tutorials daily
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If you are interested in: – Python – Machine Learning – MLOps – CV/NLP – LLMs Find me → @Sumanth_077 Everyday, I share tutorials on above topics! Like/RT the first tweet to help this reach more people!
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Machine Learning for Beginners: Complete Guide to ML Techniques and Projects
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3. Machine Learning for Beginners This covers and helps you learn: – Various ML Techniques
– Building your first ML Project right from data collection to create a web app for a trained model
– NLP Techniques
– Times Series
– Reinforcement Learning https://
microsoft.github.io/ML-For-Beginne
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Data Science for Beginners: Complete Learning Guide and Fundamentals
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2. Data Science for Beginners This covers and helps you learn: – Data Science Basics & Ethics
– Statistics
– SQL & NOSQL
– Data Preparation & Visualization
– Data Analysis
– Complete Data Science Lifecycle Check this out: https://
microsoft.github.io/Data-Science-F
or-Beginners/#/
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AI for Beginners: NLP, Computer Vision, and Key Terminologies
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1. AI for Beginners Get a basic idea of what it is like to get into AI. – Terminologies
– Basics of NLP
– Basics of Computer Vision https://
microsoft.github.io/AI-For-Beginne
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Microsoft Free Data Science and Machine Learning Courses
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Microsoft is offering FREE courses to jumpstart your career in Data Science and Machine Learning. Here are 3 free courses you don't want to miss:
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Python ML MLOps CV NLP LLMs Daily Tutorials
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If you are interested in: – Python – Machine Learning – MLOps – CV/NLP – LLMs Find me → @Sumanth_077 Everyday, I share tutorials on above topics! Like/RT the first tweet to help this reach more people!
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Implementing _predict_single Method for KNN Classification
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Finally a '_predict_single' method as mentioned it predicts the class label for a single data point This is done by: 1. Calculating the distance between one point to all training examples 2. Selecting the k-nearest Neighbours, & returning the most common class label among them
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Predict Method for Class Labels Using Single Point Prediction
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A 'predict' method that predicts the class labels for a set of data points. It calls '_predict_single' method that actually predicts the class label for a single data point.
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Implementing fit Method and Euclidean Distance in KNN
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Next define the "fit" method that takes the training data(X) and it's corresponding labels(y) and stores them. This is the reason why the computation cost is high as it stores all the training data! And also a method to calculates the euclidean distance between two data points.