Mlearning.ai

NOVEMBER 29, 2023

How to Use Machine Learning (ML) for Time Series Forecasting — NIX United The modern market pace calls for a respective competitive edge. Data forecasting has come a long way since formidable data processing-boosting technologies such as machine learning were introduced. Some of them may even be deemed outdated by now.

Machine Learning 52

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DrivenData Labs

APRIL 10, 2024

In the Kelp Wanted challenge, participants were called upon to develop algorithms to help map and monitor kelp forests. Winning algorithms will not only advance scientific understanding, but also equip kelp forest managers and policymakers with vital tools to safeguard these vulnerable and vital ecosystems.

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Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

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Heartbeat

OCTOBER 23, 2023

Revolutionizing Healthcare through Data Science and Machine Learning Image by Cai Fang on Unsplash Introduction In the digital transformation era, healthcare is experiencing a paradigm shift driven by integrating data science, machine learning, and information technology.

Machine Learning 52

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DrivenData Labs

MARCH 28, 2023

I am involved in an educational program where I teach machine and deep learning courses. Machine learning is my passion and I often take part in competitions. Before my PhD, I completed a Masters degree in biomedical engineering at Tsinghua University and worked as an algorithm engineer at SenseTime.

Machine Learning 130

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Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. The resulting structured data is then used to train a machine learning algorithm. There are a lot of image annotation techniques that can make the process more efficient with deep learning.

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DagsHub

APRIL 21, 2024

Source: [link] Similarly, while building any machine learning-based product or service, training and evaluating the model on a few real-world samples does not necessarily mean the end of your responsibilities. MLOps tools play a pivotal role in every stage of the machine learning lifecycle. What is MLOps?

Machine Learning 59

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DrivenData Labs

MAY 24, 2023

The NAS is investing in new ways to bring vast amounts of data together with state-of-the-art machine learning to improve air travel for everyone. Federated learning is a technique for collaboratively training a shared machine learning model across data from multiple parties while preserving each party's data privacy.

Machine Learning 225

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Heartbeat

FEBRUARY 20, 2023

First-time project and model registration Photo by Isaac Smith on Unsplash The world of machine learning and data science is awash with technicalities. Machine learning problems could grow to such an extent that you constantly lose track of what you are doing. One problem that is particularly prevalent is model tracking.

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Pickl AI

MAY 24, 2023

This may include for instance in Machine Learning, Data Science, Data Visualisation, image and Data Manipulation. Its modified feature includes the cross-validation that allowing it to use more than one metric. NumPy NumPy is one of the most popular Python Libraries for Machine Learning in Python.

Data Science 52

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Pickl AI

NOVEMBER 2, 2023

A cheat sheet for Data Scientists is a concise reference guide, summarizing key concepts, formulas, and best practices in Data Analysis, statistics, and Machine Learning. These reference guides condense complex concepts, algorithms, and commands into easy-to-understand formats.

Data Scientist 52

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DrivenData Labs

JUNE 19, 2023

The challenge ¶ The objective of the VisioMel Challenge was to explore the feasibility of an algorithm that can predict the recurrence of melanomas diagnosed at a localized stage. The results already show that the algorithms are at least on par with the traditional prognostic factors.

Deep Learning 130

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DataRobot

DECEMBER 20, 2021

Image recognition is one of the most relevant areas of machine learning. Deep learning makes the process efficient. it’s possible to build a robust image recognition algorithm with high accuracy. We embedded best practices and various deep learning models to support image data. DataRobot Visual AI.

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DrivenData Labs

JANUARY 11, 2023

The results of this GCMS challenge could not only support NASA scientists to more quickly analyze data, but is also a proof-of-concept of the use of data science and machine learning techniques on complex GCMS data for future missions. The third-place winner combined both feature engineering and neural network feature learning.

Deep Learning 130

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Heartbeat

DECEMBER 19, 2023

Selection of Recommender System Algorithms: When selecting recommender system algorithms for comparative study, it's crucial to incorporate various methods encompassing different recommendation approaches. This diversity ensures a comprehensive understanding of each algorithm's performance under various scenarios.

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Heartbeat

MARCH 27, 2023

This was necessary as the registry is where a machine learning practitioner can keep track of experiments and model versions. Sometimes this is a good thing as it may be beneficial to the outcome that a data scientist or machine learning practitioner may desire. Have you tried Comet?

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Mlearning.ai

MAY 23, 2023

An interdisciplinary field that constitutes various scientific processes, algorithms, tools, and machine learning techniques working to help find common patterns and gather sensible insights from the given raw input data using statistical and mathematical analysis is called Data Science. What is Data Science?

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Heartbeat

MAY 29, 2023

We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods. LLMs use a combination of machine learning and human input; image from OpenAI Data preparation and preprocessing The first, and perhaps most crucial, step in LLM training is data preparation.

Machine Learning 78

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PyImageSearch

JANUARY 23, 2023

In this tutorial, you will learn the magic behind the critically acclaimed algorithm: XGBoost. But all of these algorithms, despite having a strong mathematical foundation, have some flaws or the other. The goal is to nullify the abstraction created by packages as much as possible. What Is XGBoost?

Deep Learning 107

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Mlearning.ai

APRIL 11, 2023

Use the cross validation technique to provide a more accurate estimate of the generalization error. Double descent phenomenon There are two different manifestations of the double descent phenomenon in machine learning. Increase the size of training data. L1 norm and L2 norm).

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Pickl AI

APRIL 26, 2024

It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques. Statistical Analysis: Learn the Central Limit Theorem, correlation, and basic calculations like mean, median, and mode. The median is the middle value in a sorted list of numbers.

Data Analyst 52

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. Journal of machine learning research 9, no. probability.

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Mlearning.ai

JUNE 27, 2023

To address such tasks and uncover behavioral patterns, we turn to a powerful technique in Machine Learning called Clustering. Originally used in Data Mining, clustering can also serve as a crucial preprocessing step in various Machine Learning algorithms. How would we tackle this challenge? K = 3 ; 3 Clusters.

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Mlearning.ai

FEBRUARY 23, 2023

Learning about perceptrons is important for building a foundation in neural network concepts and understanding the potential of more advanced models for solving complex problems. Read More Linear Regression from Scratch with Gradient Descent Smart Aspects of CatBoost Algorithm How Fast Is Your Light GBM?

Python 52

Python Cross Validation Machine Learning Machine Learning 52

Mlearning.ai

FEBRUARY 15, 2024

Let’s use those fancy algorithms to make predictions from our data. There are many algorithms which can be used from this task ranging from Logistic regression to Deep learning. Later we will use another algorithm as well to see if we can further improve the result. You can refer part-I and part-II of this article.

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