ODSC - Open Data Science

FEBRUARY 20, 2023

He received the Ulf Grenander Prize from the American Mathematical Society in 2021, the IEEE John von Neumann Medal in 2020, the IJCAI Research Excellence Award in 2016, the David E. His research interests bridge the computational, statistical, cognitive, biological, and social sciences.

Machine Learning 96

Machine Learning Machine Learning Data Science Python 96

AWS Machine Learning Blog

NOVEMBER 22, 2023

The task involved writing Python code to read data, transform it, and then visualize it in an interesting map. Read and summarize the data To give the agent context about the dataset, we prompt Claude 2 to write Python code that reads the data and provides a summary relevant to our task. The full list is available in the prompts.py

Python 119

Python AWS Data Scientist AI 119

AWS Machine Learning Blog

JANUARY 17, 2024

Solution overview In this blog, we will walk through the following scenarios : Deploy Llama 2 on AWS Inferentia instances in both the Amazon SageMaker Studio UI, with a one-click deployment experience, and the SageMaker Python SDK. Fine-tune Llama 2 on Trainium instances in both the SageMaker Studio UI and the SageMaker Python SDK.

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AWS Python Machine Learning Machine Learning 129

AWS Machine Learning Blog

FEBRUARY 28, 2023

In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. For example, in the healthcare industry, ML-driven analytics can be used for diagnostic assistance and personalized medicine, while in health insurance, it can be used for predictive care management.

ML 100

ML ML AWS Machine Learning 100

AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

AWS 113

AWS ML ML Clustering 113

Mlearning.ai

JANUARY 27, 2023

How to read an image in Python using OpenCV — 2023 2. Rotating and Scaling Images using cv2 — a fun Python application — 2023 5. How to use mouse clicks to draw circles in Python using OpenCV — easy project — 2023 6. How to use mouse clicks to draw circles in Python using OpenCV — easy project — 2023 6.

Deep Learning 98

Deep Learning Deep Learning Python Data Scientist 98

DagsHub

APRIL 7, 2024

These pipelines cover the entire lifecycle of an ML project, from data ingestion and preprocessing, to model training, evaluation, and deployment. Adopted from [link] In this article, we will first briefly explain what ML workflows and pipelines are. around the world to streamline their data and ML pipelines.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

DagsHub

JULY 25, 2024

This guarantees businesses can fully utilize deep learning in their AI and ML initiatives. You can make more informed judgments about your AI and ML initiatives if you know these platforms' features, applications, and use cases. Integration: Strong integration with Python, supporting popular libraries such as NumPy and SciPy.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 96

ML ML Deep Learning Deep Learning 96

Pickl AI

MAY 16, 2023

Python, Data Mining, Analytics and ML are one of the most preferred skills for a Data Scientist. For example, if you are a Data Scientist, then you should add keywords like Python, SQL, Machine Learning, Big Data and others. Expansive Hiring The IT and service sector is actively hiring Data Scientists. Wrapping it up !!!

Data Scientist 52

Data Scientist Data Science SQL Python 52

Mlearning.ai

MAY 15, 2023

describe() count 9994 mean 2017-04-30 05:17:08.056834048 min 2015-01-03 00:00:00 25% 2016-05-23 00:00:00 50% 2017-06-26 00:00:00 75% 2018-05-14 00:00:00 max 2018-12-30 00:00:00 Name: Order Date, dtype: object Average sales per year df['year'] = df['Order Date'].apply(lambda Yearly average sales. Convert it into a graph.

Data Science 52

Data Science Machine Learning Machine Learning AI 52

DrivenData Labs

DECEMBER 13, 2022

head () Out[4]: uid latitude longitude date split 0 aabm 39.080319 -86.430867 2018-05-14 train 1 aabn 36.559700 -121.510000 2016-08-31 test 2 aacd 35.875083 -78.878434 2020-11-19 train 3 aaee 35.487000 -79.062133 2016-08-24 train 4 aaff 38.049471 -99.827001 2019-07-23 train In [5]: metadata. In [4]: metadata = pd. value_counts ().

ML 130

ML ML Python Deep Learning 130

How to Learn Machine Learning

DECEMBER 4, 2022

In 2016, Google released an open-source software called AutoML. Some common coding languages include C++, Java, Python , and SQL. Finally, machine learning (ML) is also being used to write code. ML is a type of AI that allows systems to learn from data and improve their performance over time.

AI 52

AI AI Machine Learning Machine Learning 52

Mlearning.ai

JULY 9, 2023

Abstract Polars is a fast-growing open-source data frame library that is rapidly becoming the preferred choice for data scientists and data engineers in Python. It is available in multiple languages: Python, Rust, and NodeJS. If you are looking for a fast and intuitive data frame library for Python, then Polars is a great option.

Data Analysis 52

Data Analysis Data Analysis Python Data Scientist 52

DataRobot Blog

MARCH 10, 2022

The “Fourth Industrial Revolution” was coined by Klaus Schwab of the World Economic Forum in 2016. Python is unarguably the most broadly used programming language throughout the data science community. Native Python Support for Snowpark. Consuming AI/ML Insights for Faster Decision Making.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 21, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. You can use either method to generate the linearized text from the document using the latest version of Amazon Textract Textractor Python library.

AI 117

AI AI Database AWS 117

Mlearning.ai

APRIL 10, 2023

2016) Data Management : By allowing clustering to occur locally, edge devices in the network can enable near-real-time data analysis in order to make data-driven decisions Energy : Clustering methods have been known to be more energy efficient when it comes to data transmission and processing (Loganathan & Arumugan, 2021). 2016.2545384.

Clustering 52

Clustering Internet of Things Algorithm Machine Learning 52

Mlearning.ai

MARCH 22, 2023

It was so much easier when one just needed to know python, sci-kit learn, pandas, tensorflow, and pytorch. The number of AI applications and programming languages that one needs to know to stay competent has drastically increased. Google Apps Scripts is a combination of Javascript and html, the Google scripts scripting language (.gs)

Data Scientist 52

Data Scientist Azure Python Analytics 52

AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 52

ML ML Deep Learning Deep Learning 52

Heartbeat

SEPTEMBER 13, 2023

Here's an example of calculating feature importance using permutation importance with scikit-learn in Python: from sklearn.inspection import permutation_importance # Fit your model (e.g., Alibi Alibi is an open-source Python library for algorithmic transparency and interpretability. Russell, C. & & Watcher, S. Singh, S. &

Machine Learning 52

Machine Learning Machine Learning AI AI 52

DagsHub

DECEMBER 16, 2024

In the fraud detection example, to effectively translate ML metrics into business-relevant information, we need to understand how the model’s behavior impacts business objectives. In other words, the outcomes of ML models should be equitable across different groups, even if there were historical biases in the training data.

Machine Learning 52

Machine Learning Machine Learning Python Deep Learning 52

Mlearning.ai

MARCH 9, 2023

We implemented the MBD approach using the Python programming language, with the scikit-learn and NetworkX libraries for feature selection and structure learning, respectively. 2018; Papernot et al., We also ensured that the selected images were not part of the training set for the MBD model, to avoid any bias in the results. Papernot, N.,

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Mlearning.ai

FEBRUARY 11, 2023

A Simple Step-to-Step Guide to Chi-Square Tests in Python Introduction In our last article , we used the t-test. Photo by Mikhail Nilov on Pixels Overview In this article, we will provide a step-to-step guide on how to perform Chi-Square tests in Python. 2016) Statistics in Plain English. We will accept the null hypothesis.

Python 52

Python ML ML Data Science 52

Mlearning.ai

APRIL 28, 2023

This API call can literally be anything, e.g. executing a Python script, calling another neural network, and so on. When detecting the execute API token “→” the decoding process is interrupted and the API is called with its input. You name it. In the end, the response just needs to be a single text sequence. 2020 ), SVAMP ( Patel et al.,

Deep Learning 52

Deep Learning Deep Learning Python ML 52

AWS Machine Learning Blog

NOVEMBER 11, 2024

Solution overview SageMaker JumpStart is a robust feature within the SageMaker machine learning (ML) environment, offering practitioners a comprehensive hub of publicly available and proprietary foundation models (FMs). We then also cover how to fine-tune the model using SageMaker Python SDK. You can access the Meta Llama 3.2

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AI AI ML ML 115