Launchpad

Intro to ML (Part 1 of Intro to Machine Learning (Supervised Learning with Linear Models)

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AWS Database Services (Part 1 of ML Tools)

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Basics of Production (Part 1 of Production)

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Pretrained Models for Image Classification and Object Detection (Part 3 of Computer Vision)

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Support Vector Machines(Part 4 of Intro to Machine Learning (Supervised Learning with Linear Models)

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Random Forest (Part 3 of Supervised Learning with Non-Linear Models)

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Intro to FB Prophet (Part 4 of Time Series Analysis)

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Feature Importance with MLJAR (Part 4 of AutoML)

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Logistic Regression (Part 3 of Intro to Machine Learning (Supervised Learning with Linear Models)

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Gradient Boosted Machines (Part 4 of Supervised Learning with Non-Linear Models)

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Transfer Learning in Computer Vision (Part 4 of Computer Vision)

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K Nearest Neighbours (Part 2 of Supervised Learning with Non-Linear Models)

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Principal Component Analysis (Part 2 of Unsupervised Learning)

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Intro to Apache Spark (Part 2 of ML Tools)

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Decision Trees (Par 1 of Supervised Learning with Non-Linear Models)

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Data Cleaning & EDA (Part 2 of Time Series Analysis)

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Linear Regression (Part 2 of Intro to Machine Learning (Supervised Learning with Linear Models)

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Fundamentals of Project Design (Part 2 of Production)

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Building a Convolutional Neural Network (Part 2 of Computer Vision)

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Introduction to Time Series Data (Part 1 of Time Series Analysis)

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Traditional ML Techniques (Part 3 of Time Series Analysis)

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Introduction to Recommendation Systems (Part 1 of Recommendation Systems)

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Fundamentals of Computer Vision (Part 1 of Computer Vision)

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K Means (Part 1 of Unsupervised Learning)

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Introduction to Pandas (Part 2 of Introduction to Data Science Libraries)

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Introduction to Numpy (Part 1 of Introduction to Data Science Libraries)

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Fellowship CoMAT, Chain of Mathematically Annotated Thought Improves Mathematical Reasoning

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Fellowship LLaRA, Supercharging Robot Learning Data for Vision-Language Policy

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Fellowship UnSAM, Unsupervised Segmentation Anything Model A new approach to Image Segmentation

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Fellowship MiniCPM, Unveiling Small Language Models with Scalable Training Strategies

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