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

Machine Learning Machine Learning Decision Trees Data Science 225

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.

Cross Validation 64

Cross Validation AI AI Machine Learning 64

Mlearning.ai

FEBRUARY 15, 2024

This cross-validation results shows without regularization. Decision Tree This will create a predictive model based on simple if-else decisions. So far, the Decision tree classifier model with max_depth =10 and the min_sample_split = 0.005 has given the best result. Why am I using regularization?

Data Science 52

Data Science Decision Trees Exploratory Data Analysis Cross Validation 52

Pickl AI

MAY 24, 2023

This may include for instance in Machine Learning, Data Science, Data Visualisation, image and Data Manipulation. As the collection of Python libraries are huge, you might be faced with the need to make difficult decision on which library to choose from. What to consider when choosing a Python Library?

Data Science 52

Data Science Python Machine Learning Machine Learning 52

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

Data Analyst Data Analysis Data Analysis Machine Learning 52

Mlearning.ai

FEBRUARY 15, 2023

Figure 1 Preprocessing Data preprocessing is an essential step in building a Machine Learning model. Some important things that were considered during these selections were: Random Forest : The ultimate feature importance in a Random forest is the average of all decision tree feature importance. link] Ganaie, M.

Cross Validation 52

Cross Validation Decision Trees Natural Language Processing Algorithm 52

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. It serves as a handy quick-reference tool to assist data professionals in their work, aiding in data interpretation, modeling , and decision-making processes.

Data Scientist 52

Data Scientist Data Science Data Visualization Machine Learning 52

Pickl AI

FEBRUARY 4, 2024

Predictive Analytics: Leverage machine learning algorithms for accurate predictions. This makes Alteryx an indispensable tool for businesses aiming to glean insights and steer their decisions based on robust data. Predictive modeling Alteryx elevates predictive modeling with integrated machine learning algorithms and AutoML.

Data Preparation 52

Data Preparation Tableau Data Visualization SQL 52

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

Machine Learning Machine Learning ML ML 52

Mlearning.ai

NOVEMBER 30, 2023

Mastering Tree-Based Models in Machine Learning: A Practical Guide to Decision Trees, Random Forests, and GBMs Image created by the author on Canva Ever wondered how machines make complex decisions? Just like a tree branches out, tree-based models in machine learning do something similar.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Data Science 52

Mlearning.ai

FEBRUARY 10, 2024

Unlocking Predictive Power: How Bayes’ Theorem Fuels Naive Bayes Algorithm to Solve Real-World Problems [link] Introduction In the constantly shifting realm of machine learning, we can see that many intricate algorithms are rooted in the fundamental principles of statistics and probability.

Algorithm 52

Algorithm Decision Trees Cross Validation Machine Learning 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. Decision trees are more prone to overfitting.

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52

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

Machine Learning Machine Learning ML ML 59

Mlearning.ai

APRIL 13, 2023

Photo by Robo Wunderkind on Unsplash In general , a data scientist should have a basic understanding of the following concepts related to kernels in machine learning: 1. Machine learning algorithms rely on mathematical functions called “kernels” to make predictions based on input data. What are kernels? Linear Kernels 2.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Support Vector Machines 52

Heartbeat

OCTOBER 31, 2023

The goal of bagging is to enhance the performance and accuracy of machine learning models. Before continuing, revisit the lesson on decision trees if you need help understanding what they are. Cross-validation is recommended as best practice to provide reliable results because of this.

Decision Trees 52

Decision Trees Cross Validation Deep Learning Deep Learning 52

Iguazio

JUNE 25, 2023

Some of the most common performance metrics for machine learning models include: Classification Model Metrics A classification model is a model that is trained to assign class labels to input data based on certain patterns or features. They vary according to the model type and use cases.

ML 52

ML ML Clustering Cross Validation 52

The MLOps Blog

JUNE 6, 2023

We’re about to learn how to create a clean, maintainable, and fully reproducible machine learning model training pipeline. The preprocessing stage involves cleaning, transforming, and encoding the data, making it suitable for machine learning algorithms. Too good to be true? Not at all.

ML 52

ML ML Cross Validation Machine Learning 52

Dataconomy

SEPTEMBER 1, 2023

Apart from many areas in our lives, hybrid machine learning techniques can help us with effective heart disease prediction. So how can the technology of our time, machine learning, be used to improve the quality and length of human life? According to the World Health Organization , heart disease takes an estimated 17.9

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195

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

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

PyImageSearch

JANUARY 23, 2023

The reasoning behind that is simple; whatever we have learned till now, be it adaptive boosting, decision trees, or gradient boosting, have very distinct statistical foundations which require you to get your hands dirty with the math behind them. The goal is to nullify the abstraction created by packages as much as possible.

Deep Learning 107

Deep Learning Deep Learning Algorithm Decision Trees 107

Mlearning.ai

JULY 14, 2023

Random forests inherit the benefits of a decision tree model whilst improving upon the performance by reducing the variance. —  Jeremy Jordan Random Forest is a popular and powerful ensemble learning algorithm that combines multiple decision trees to generate accurate and stable predictions.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Cross Validation 52