As a bonus, get the code to apply feature extraction anywhere Image created by DALL·E 3 based on the prompt “Draw a pack of futuristic grey wolves at night by the beach.”This is the last part of my series of nature-inspired articles. Earlier, I had talked about algorithms inspired by genetics, swarm, bees, and ants.…
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Do you remember that one data science course you signed up for but never got around to finishing? Well, you’re not alone.
Most data science beginners enroll in one or more courses: free or paid. But because data science courses typically cover a wide range of topics—from programming to data…
In artificial intelligence, integrating multimodal inputs for video reasoning stands as a frontier, challenging yet ripe with potential. Researchers increasingly focus on leveraging diverse data types – from visual frames and audio snippets to more complex 3D point clouds – to enrich AI’s understanding and interpretation of the world. This endeavor aims to mimic human…
Featurizing time series data into a standard tabular format for classical ML models and improving accuracy using AutoML Source: Ahasanara AkterThis article delves into enhancing the process of forecasting daily energy consumption levels by transforming a time series dataset into a tabular format using open-source libraries. We explore the application of a popular multiclass classification…
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Data orchestration has become a critical component of modern data engineering, allowing teams to streamline and automate their data workflows. While Apache Airflow is a widely used tool known for its flexibility and strong community support. However, there are several other alternatives that offer unique features and benefits.
In this…
The progress and development of artificial intelligence (AI) heavily rely on human evaluation, guidance, and expertise. In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet.
Similarly, in robotics, reinforcement learning often relies on…
Whether you’re applying to your first internship to running a multidisciplinary team of analysts and engineers, data science careers come with their own specific set of challenges. Some of these might be more exciting than others, and others can be downright tedious—that’s true in any job, of course—but we believe in framing all of these…
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Everybody wants a bite of the generative AI cake, from software developers to non-technical business leaders. Having all the information and skills required to take generative AI to the next level in your career or organization is all you need. You can now get this information with Amazon's free courses…
Artificial intelligence has significantly advanced in developing systems that can interpret and respond to multimodal data. At the forefront of this innovation is Lumos, a groundbreaking multimodal question-answering system designed by researchers at Meta Reality Labs. Unlike traditional systems, Lumos distinguishes itself by its exceptional ability to extract and understand text from images, enhancing the…
Imports We import modules from Hugging Face’s transforms, peft, and datasets libraries. from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline from peft import prepare_model_for_kbit_training from peft import LoraConfig, get_peft_model from datasets import load_dataset import transformers Additionally, we need the following dependencies installed for some of the previous modules to work. !pip install auto-gptq !pip install optimum !pip…