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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

Learning the various categories of machine learning, associated algorithms, and their performance parameters is the first step of machine learning. Machine learning is broadly classified into three types – Supervised. In supervised learning, a variable is predicted. Semi-Supervised Learning.

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What Is a Transformer Model?

Hacker News

“Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

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How MLOps Work in the Era of Large Language Models

ODSC - Open Data Science

Given they’re built on deep learning models, LLMs require extraordinary amounts of data. MLOps can help organizations manage this plethora of data with ease, such as with data preparation (cleaning, transforming, and formatting), and data labeling, especially for supervised learning approaches.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

The two most common types of supervised learning are classification , where the algorithm predicts a categorical label, and regression , where the algorithm predicts a numerical value. Things to be learned: Ensemble Techniques such as Random Forest and Boosting Algorithms and you can also learn Time Series Analysis.

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning.

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Must-Have Skills for a Machine Learning Engineer

Pickl AI

Without linear algebra, understanding the mechanics of Deep Learning and optimisation would be nearly impossible. These techniques span different types of learning and provide powerful tools to solve complex real-world problems. Neural networks are the foundation of Deep Learning techniques.

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Dogs vs Cats Audio Classification

Mlearning.ai

Using PyTorch Deep Learning Framework and CNN Architecture Photo by Andrew S on Unsplash Motivation Build a proof-of-concept for Audio Classification using a deep-learning neural network with PyTorch framework. This is inherently a supervised learning problem. Data Source here.