Towards AI

JULY 19, 2023

Basically crack is a visible entity and so image-based crack detection algorithms can be adapted for inspection. Deep learning algorithms can be applied to solving many challenging problems in image classification. Deep learning algorithms can be applied to solving many challenging problems in image classification. Yi, and J.-K.

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Deep Learning Deep Learning Algorithm AI 98

Dataconomy

MAY 8, 2023

AI drawing generators use machine learning algorithms to produce artwork What is AI drawing? You might think of AI drawing as a generative art where the artist combines data and algorithms to create something completely new. The language model for Stable Diffusion is a transformer, and it is implemented in Python.

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Artificial Intelligence Artificial Intelligence AI AI 194

AWS Machine Learning Blog

OCTOBER 9, 2023

Although the internal algorithms within Amazon Personalize have been chosen based on Amazon’s experience in the machine learning space, a personalized model doesn’t come pre-loaded with any sort of data and trains models on a customer-by-customer basis. For this post, we choose Python (User-Defined Function). DOI= [link]

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AWS Machine Learning Machine Learning Python 121

Pickl AI

JANUARY 23, 2023

People don’t even need the in-depth knowledge of the various machine learning algorithms as it contains pre-built libraries. It supports languages like Python and R and processes the data with the help of data flow graphs. It is an open-source framework that is written in Python and can efficiently operate on both GPUs and CPUs.

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Machine Learning Machine Learning ML ML 52

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Understanding the robustness of image segmentation algorithms to adversarial attacks is critical for ensuring their reliability and security in practical applications.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Hacker News

JANUARY 9, 2024

Sometimes it’s a story of creating a superalgorithm that encapsulates decades of algorithmic development. One very simple example (introduced in 2015) is Nothing : Another, introduced in 2020, is Splice : An old chestnut of Wolfram Language design concerns the way infinite evaluation loops are handled. Let’s start with Python.

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Python Algorithm Machine Learning Machine Learning 181

AWS Machine Learning Blog

APRIL 25, 2024

The most common techniques used for extractive summarization are term frequency-inverse document frequency (TF-IDF), sentence scoring, text rank algorithm, and supervised machine learning (ML). Use the evaluation algorithm with either built-in or custom datasets to evaluate your LLM model.

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Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. Try the new interactive demo to explore similarities and compare them between 2015 and 2019 sense2vec (Trask et. Interestingly, “to ghost” wasn’t very common in 2015.

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Natural Language Processing Data Scientist Machine Learning Machine Learning 52

DagsHub

JULY 25, 2024

TensorFlow The Google Brain team created the open-source deep learning framework TensorFlow, which was made available in 2015. TensorFlow implements a wide range of deep learning and machine learning algorithms and is well-known for its adaptability and extensive ecosystem.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

AWS Machine Learning Blog

FEBRUARY 28, 2023

One of the challenges of working with categorical data is that it is not as amenable to being used in many machine learning algorithms. To overcome this, we use one-hot encoding, which converts each category in a column to a separate binary column, making the data suitable for a wider range of algorithms.

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AWS Machine Learning Blog

APRIL 18, 2023

Solution overview In the following sections, we provide a step-by-step demonstration for fine-tuning an LLM for text generation tasks via both the JumpStart Studio UI and Python SDK. learning_rate – Controls the step size or learning rate of the optimization algorithm during training.

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ML ML Deep Learning Deep Learning 96

Mlearning.ai

JUNE 5, 2023

Note : This blog is more biased towards python as it is the language most developers use to get started in computer vision. Python / C++ The programming language to compose our solution and make it work. Why Python? Easy to Use: Python is easy to read and write, which makes it suitable for beginners and experts alike.

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Deep Learning Deep Learning Python Machine Learning 52

Explosion

NOVEMBER 23, 2021

In practice, the rule-finding algorithm is a bit more complex, since there may be multiple shared substrings. This is accounted for by using a recursive version of the algorithm above. Rather than simply replacing the string afge by af , we apply the algorithm to these two substrings as well. a prefix of length n ; 2.

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Algorithm Python Machine Learning Machine Learning 52

Heartbeat

JULY 24, 2023

pip install dicom2nifti In a Python shell type: import dicom2nifti dicom2nifti.convert_directory("path to.dcm images"," path where results to be stored") And boom! This algorithm also does tissue chopping to remove computational complexities. This particular algorithm is not restricted to human anatomy.

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Deep Learning Deep Learning AI AI 52

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. It advances the scalability of ML in real-world applications by using algorithms to improve model performance and reproducibility. What is MLOps?

Data Science 68

Data Science Machine Learning Machine Learning ML 68

Explosion

MAY 10, 2016

The pay-off is the.pipe() method, which adds data-streaming capabilities to spaCy: import spacy nlp = spacy.load('de') for doc in nlp.pipe(texts, n_threads=16, batch_size=10000): analyse_text(doc) My favourite post on the Zen of Python iterators was written by Radim, the creator of Gensim. The Python unicode object is also very useful.

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Python Natural Language Processing Machine Learning Machine Learning 40

Pickl AI

AUGUST 22, 2024

Discover its dynamic computational graphs, ease of debugging, strong community support, and seamless integration with popular Python libraries for enhanced development. Pythonic Nature PyTorch is designed to be intuitive and closely resembles standard Python programming.

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Deep Learning Deep Learning Machine Learning Machine Learning 52

Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

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Database AWS ETL SQL 158

Hacker News

MARCH 19, 2025

The Allen Institute for AI introduced Semantic Scholar way back in 2015; it was among the earliest platforms to rank and predict research relevance with machine learning rather than raw citation counts. Going from a demo in a Jupyter notebook (used to write Python code) to getting something that can run at scale is a lot of work.

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AI AI Data Analysis Data Analysis 125

Pickl AI

JULY 3, 2023

billion in 2015 and reached around $26.50 Explore their features, functionalities, and best practices for creating reports, dashboards, and visualizations. Develop programming skills: Enhance your programming skills, particularly in languages commonly used in BI development such as SQL, Python, or R. billion in 2021.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

AWS Machine Learning Blog

APRIL 18, 2023

Solution overview In the following sections, we provide a step-by-step demonstration for fine-tuning an LLM for text generation tasks via both the JumpStart Studio UI and Python SDK. learning_rate – Controls the step size or learning rate of the optimization algorithm during training.

ML 52

ML ML Deep Learning Deep Learning 52

phData

MARCH 6, 2023

There is no need to be a Python programmer or to have an advanced degree in mathematics or computer science (although these things certainly don’t hurt). Through various algorithms, the tree places records from the data set into binary groups (yes/no, 0/1, true/false) until a final designation is achieved.

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Decision Trees Analytics Analytics Data Science 52

Chatbots Life

MAY 12, 2023

We can ask the model to generate a python function or a recipe for a cheesecake. Here is a brief description of the algorithm: OpenAI collected prompts submitted by the users to the earlier versions of the model. This approach with the rewards system based on human feedback is applied to GPT3 to create InstructGPT.

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Snorkel AI

FEBRUARY 27, 2023

But I want to at least give our perspective on what motivated us back in 2015 to start talking about this and to start studying it back at Stanford, where the Snorkel team started: this idea of a shift from model-centric to data-centric AI development. So we’re going to be hearing about lots of topics.

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AI AI Machine Learning Machine Learning 52

Snorkel AI

FEBRUARY 27, 2023

But I want to at least give our perspective on what motivated us back in 2015 to start talking about this and to start studying it back at Stanford, where the Snorkel team started: this idea of a shift from model-centric to data-centric AI development. So we’re going to be hearing about lots of topics.

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AI AI Machine Learning Machine Learning 52

Towards AI

APRIL 26, 2025

Dataset Overview 🌫 Air Quality Data in India (20152020) 📌 Link: DATASET 📝 Overview This dataset contains daily air quality data from major cities across India, collected between 2015 and 2020. It includes concentrations of various pollutants, meteorological parameters, and calculated AQI values.

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Machine Learning Machine Learning ML ML 56

AWS Machine Learning Blog

NOVEMBER 26, 2024

We add the following to the end of the prompt: provide the response in json format with the key as “class” and the value as the class of the document We get the following response: { "class": "ID" } You can now read the JSON response using a library of your choice, such as the Python JSON library. The following image is of a gearbox.

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AWS Machine Learning Blog

NOVEMBER 11, 2024

We then also cover how to fine-tune the model using SageMaker Python SDK. FMs through SageMaker JumpStart in the SageMaker Studio UI and the SageMaker Python SDK. Fine-tune using the SageMaker Python SDK You can also fine-tune Meta Llama 3.2 models using the SageMaker Python SDK. You can access the Meta Llama 3.2

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