Ocean Protocol

SEPTEMBER 20, 2023

This challenge asked participants to gather their own data on their favorite DeFi protocol. From there, participants were asked to conduct exploratory data analysis, explore recommendations to the protocol, and dive into key metrics and user retention rates that correlate and precede the success of a given protocol.

Clustering 98

Clustering Exploratory Data Analysis Data Scientist Data Analysis 98

ODSC - Open Data Science

OCTOBER 18, 2023

The process begins with a careful observation of customer data and an assessment of whether there are naturally formed clusters in the data. It continues with the selection of a clustering algorithm and the fine-tuning of a model to create clusters.

Machine Learning 52

Machine Learning Machine Learning Clustering Data Science 52

Dataconomy

JUNE 29, 2023

These packages are built to handle various aspects of machine learning, including tasks such as classification, regression, clustering, dimensionality reduction, and more. These packages cover a wide array of areas including classification, regression, clustering, dimensionality reduction, and more.

Machine Learning 113

Machine Learning Machine Learning Deep Learning Deep Learning 113

Mlearning.ai

MAY 23, 2023

Blind 75 LeetCode Questions - LeetCode Discuss Data Manipulation and Analysis Proficiency in working with data is crucial. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).

Data Science 52

Data Science Data Scientist Apache Hadoop Machine Learning 52

Pickl AI

APRIL 26, 2024

I would perform exploratory data analysis to understand the distribution of customer transactions and identify potential segments. Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. What approach would you take?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Dataconomy

JULY 28, 2023

How to become a data scientist Data transformation also plays a crucial role in dealing with varying scales of features, enabling algorithms to treat each feature equally during analysis Noise reduction As part of data preprocessing, reducing noise is vital for enhancing data quality.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Pickl AI

FEBRUARY 12, 2024

Unsupervised learning algorithms, on the other hand, operate on unlabeled data and identify patterns and relationships without explicit supervision. Clustering algorithms such as K-means and hierarchical clustering are examples of unsupervised learning techniques. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

JULY 18, 2023

Dealing with large datasets: With the exponential growth of data in various industries, the ability to handle and extract insights from large datasets has become crucial. Data science equips you with the tools and techniques to manage big data, perform exploratory data analysis, and extract meaningful information from complex datasets.

Computer Science 52

Computer Science Computer Science Data Science Machine Learning 52

Pickl AI

JULY 25, 2023

Their primary responsibilities include: Data Collection and Preparation Data Scientists start by gathering relevant data from various sources, including databases, APIs, and online platforms. They clean and preprocess the data to remove inconsistencies and ensure its quality.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

FEBRUARY 28, 2023

As a data scientist at Cars4U, I had to come up with a pricing model that can effectively predict the price of used cars and can help the business in devising profitable strategies using differential pricing. In this analysis, I: provided summary statistics and exploratory data analysis of the data.

Python 52

Python EDA Exploratory Data Analysis Data Analysis 52

Pickl AI

JULY 17, 2023

Therefore, it mainly deals with unlabelled data. The ability of unsupervised learning to discover similarities and differences in data makes it ideal for conducting exploratory data analysis. Market-Based Analysis can be considered a typical example of an Association rule.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

IBM Journey to AI blog

DECEMBER 20, 2023

Unsupervised machine learning Unsupervised learning algorithms—like Apriori, Gaussian Mixture Models (GMMs) and principal component analysis (PCA)—draw inferences from unlabeled datasets, facilitating exploratory data analysis and enabling pattern recognition and predictive modeling.

Machine Learning 83

Machine Learning Machine Learning Supervised Learning Clustering 83

Pickl AI

JULY 20, 2023

Kaggle datasets) and use Python’s Pandas library to perform data cleaning, data wrangling, and exploratory data analysis (EDA). Extract valuable insights and patterns from the dataset using data visualization libraries like Matplotlib or Seaborn.

Analytics 40

Analytics Analytics Big Data Big Data 40

Heartbeat

SEPTEMBER 28, 2023

In a typical MLOps project, similar scheduling is essential to handle new data and track model performance continuously. Load and Explore Data We load the Telco Customer Churn dataset and perform exploratory data analysis (EDA). Are there clusters of customers with different spending patterns? #3.

Support Vector Machines 52

Support Vector Machines Machine Learning Machine Learning ML 52

Towards AI

APRIL 19, 2024

It’s an open-source Python package for Exploratory Data Analysis of text. It has functions for the analysis of explicit text elements such as words, n-grams, POS tags, and multi-word expressions, as well as implicit elements such as clusters, anomalies, and biases.

Analytics 89

Analytics Analytics Data Analysis Data Analysis 89

DataRobot Blog

NOVEMBER 3, 2022

However, tedious and redundant tasks in exploratory data analysis, model development, and model deployment can stretch the time to value of your machine learning projects. Flexible BigQuery Data Ingestion to Fuel Time Series Forecasting. Enable Granular Forecasts with Clustering. This is where clustering comes in.

Clustering 52

Clustering Data Scientist Exploratory Data Analysis AI 52

DataRobot

DECEMBER 16, 2021

Use DataRobot’s AutoML and AutoTS to tackle various data science problems such as classification, forecasting, and regression. Not sure where to start with your massive trove of text data? Simply fire up DataRobot’s unsupervised mode and use clustering or anomaly detection to help you discover patterns and insights with your data.

AI 98

AI AI Exploratory Data Analysis Clustering 98

Data Science Blog

FEBRUARY 23, 2023

And importantly, starting naively annotating data might become a quick solution rather than thinking about how to make uses of limited labels if extracting data itself is easy and does not cost so much. In this case, original data distribution have two clusters of circles and triangles and a clear border can be drawn between them.

Supervised Learning 264

Supervised Learning Machine Learning Machine Learning Deep Learning 264

Pickl AI

JULY 10, 2023

The programming language can handle Big Data and perform effective data analysis and statistical modelling. R allows you to conduct statistical analysis and offers capabilities of statistical and graphical representation. How is R Used in Data Science?

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JUNE 12, 2023

A Data Scientist requires to be able to visualize quickly the data before creating the model and Tableau is helpful for that. Predictive analytics and modeling: With Tableau’s integration with statistical tools, you can build predictive models using techniques like regression, classification, clustering, and time series analysis.

Tableau 52

Tableau Data Science Data Scientist Data Analysis 52

DrivenData Labs

DECEMBER 7, 2023

Solvers submitted a wide range of methodologies to this end, including using open-source and third party LLMs (GPT, LLaMA), clustering (DBSCAN, K-Means), dimensionality reduction (PCA), topic modeling (LDA, BERT), sentence transformers, semantic search, named entity recognition, and more. and DistilBERT.

Natural Language Processing 130

Natural Language Processing Clustering Data Science Data Analysis 130

Mlearning.ai

AUGUST 10, 2023

We have to click on Clustered column chart visualization … because we want an easily graphs to show easy comparison between multiple categories and their respective values. Figure 19: Question 3 Visualization We can see the most searches by Brand is MG (greater than 20K) for the users. Q4: How many searches by brand and country are there?

Business Intelligence 52

Business Intelligence Business Intelligence ETL Power BI 52

Becoming Human

MAY 15, 2023

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

DataRobot Blog

DECEMBER 20, 2022

You can understand the data and model’s behavior at any time. Once you use a training dataset, and after the Exploratory Data Analysis, DataRobot flags any data quality issues and, if significant issues are spotlighted, will automatically handle them in the modeling stage. Rapid Modeling with DataRobot AutoML.

AI 59

AI AI Cross Validation Machine Learning 59

Mlearning.ai

JULY 29, 2023

It is a crucial component of the Exploration Data Analysis (EDA) stage, which is typically the first and most critical step in any data project. Why do we choose Python data visualization tools for our projects? point clouds projection on XY, XZ and YZ plane (source from FITTING A CIRCLE TO CLUSTER OF 3D POINTS ) 2.

Python 52

Python Data Visualization Data Science Exploratory Data Analysis 52