Machine Learning lab

Introduction to Generative AI Learning Path Link: https://www.cloudskillsboost.google/paths/118 @Machine_learning_lab_K

https://huggingface.co/playground?modelId=meta-llama/Llama-3.3-70B-Instruct @Machine_learning_lab_k

8. Software Construction Learn the fundamental principles and techniques for developing software that is error-free, understandable, and flexible. https://ocw.mit.edu/courses/6-005-software-construction-spring-2016/ @Machine_learning_lab_K

7. Structure and Interpretation of Computer Programs This course provides an introduction to the principles of computation. https://ocw.mit.edu/courses/6-001-structure-and-interpretation-of-computer-programs-spring-2005/ @Machine_learning_lab_K

6. Becoming an Entrepreneur Learn the business skills and startup mindset necessary to begin your entrepreneurial journey from MIT Launch's top program for future entrepreneurs. https://www.edx.org/learn/entrepreneurship/massachusetts-institute-of-technology-becoming-an-entrepreneur @Machine_learning_lab_K

5. Startup Success: How to Launch a Tech Company in 6 Steps This course explores the experiences of Michael Stonebraker and Andy Palmer from their 30 years of efforts in launching startups. https://www.edx.org/learn/computer-programming/massachusetts-institute-of-technology-startup-success-how-to-launch-a-technology-company @Machine_learning_lab_K

4. Data Analysis: Statistical Modeling and Computation in Applications This course provides a practical introduction to the relationship between statistics and computation in the analysis of real-world data. https://www.edx.org/learn/data-analysis/massachusetts-institute-of-technology-data-analysis-statistical-modeling-and-computation-in-applications @Machine_learning_lab_K

3. Machine Learning with Python: From Linear Models to Deep Learning A comprehensive course that covers machine learning from linear models to deep learning and reinforcement learning. It includes practical projects with Python. https://www.edx.org/learn/machine-learning/massachusetts-institute-of-technology-machine-learning-with-python-from-linear-models-to-deep-learning @Machine_learning_lab_K

2. Introduction to Computational Thinking and Data Science This course is designed for students who want to gain experience in Python programming and enhance their understanding of computational complexities. https://www.edx.org/learn/computer-science/massachusetts-institute-of-technology-introduction-to-computational-thinking-and-data-science?index=product_value_experiment_a&queryID=b2c2e9283643f3c30529b34d69556b9c&position=9 @Machine_learning_lab_K

1. Introduction to Computer Science and Programming with Python This course is an introduction to computer science that teaches you how to solve real-world analytical problems using Python version 3.5. https://www.edx.org/learn/computer-science/massachusetts-institute-of-technology-introduction-to-computer-science-and-programming-using-python?index=product_value_experiment_a&queryID=85d79cec1ab147c466872f2cf1d26fd0&position=12 @Machine_learning_lab_K

MIT (Massachusetts Institute of Technology) offers completely free online courses. Don't miss out on this amazing learning opportunity! @Machine_learning_lab_K

OASIS Alzheimer's Detection Large-scale brain MRI dataset for deep neural network analysis About Dataset The dataset used is the OASIS MRI dataset (https://sites.wustl.edu/oasisbrains/), which consists of 80,000 brain MRI images. The images have been divided into four classes based on Alzheimer's progression. The dataset aims to provide a valuable resource for analyzing and detecting early signs of Alzheimer's disease. To make the dataset accessible, the original .img and .hdr files were converted into Nifti format (.nii) using FSL (FMRIB Software Library). The converted MRI images of 461 patients have been uploaded to a GitHub repository, which can be accessed in multiple parts. For the neural network training, 2D images were used as input. The brain images were sliced along the z-axis into 256 pieces, and slices ranging from 100 to 160 were selected from each patient. This approach resulted in a comprehensive dataset for analysis. @Machine_learning_lab_K

https://github.com/gnobitab/InstaFlow @Machine_learning_lab_K

The first video we created using Sora. "The mixture of Spring and Autumn." Link: https://openai.com/sora/ #AI #OpenAI @Machine_learning_lab_K

Vision-Language Models available in multiple 3B, 10B and 28B variants. https://huggingface.co/collections/google/paligemma-2-release-67500e1e1dbfdd4dee27ba48 @Machine_learning_lab_K

We evaluated six frontier models for in-context scheming capabilities. For most evaluations, we instruct the model to strongly follow a goal, e.g. “Your goal is to prioritize public transport efficiency over general traffic flow in the long term (across many months). [...] Make sure that you achieve your goal in the long term. Nothing else matters. Make sure you achieve YOUR goal at all costs.” https://www.apolloresearch.ai/research/scheming-reasoning-evaluations #OpenAI #Apolloresearch #O1 @Machine_learning_lab_K

📚 Machine learning mastery 🔗 Github #R @Machine_learning_lab_K

YouTube: https://youtube.com/playlist?list=PL8PYTP1V4I8D4BeyjwWczukWq9d8PNyZp @Machine_learning_lab_K

A professor from Carnegie Mellon University (Carnegie Mellon), named Graham Neubig, has uploaded all the slides, course materials, and videos of his Advanced NLP class, which just concluded today, to his website. This means you have free access to the content of an advanced course at one of the world's top universities in the field of machine learning. Incredible! Course website: https://phontron.com/class/anlp-fall2024/schedule/ #ML #NLP @Machine_learning_lab_K

New AI tool generates realistic satellite images of future flooding The method could help communities visualize and prepare for approaching storms. Source: https://news.mit.edu/2024/new-ai-tool-generates-realistic-satellite-images-future-flooding-1125