Pickl AI

JULY 12, 2024

Exploratory Data Analysis (EDA) EDA is a crucial preliminary step in understanding the characteristics of the dataset. Techniques such as statistical summaries, data visualisation, and correlation analysis help uncover patterns, anomalies, and relationships within the data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

JUNE 7, 2023

Data Science projects require you perform different projects and track changes in your project using a version code. If you want to become an efficient Data Scientist and grab that job role you’ve been looking for, you need to work on Github for Data Science projects.

Data Science 52

Data Science Deep Learning Deep Learning Clustering 52

Heartbeat

SEPTEMBER 28, 2023

To address this challenge, data scientists harness the power of machine learning to predict customer churn and develop strategies for customer retention. Continuous Experiment Tracking with Comet ML Comet ML is a versatile tool that helps data scientists optimize machine learning experiments.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines ML 52

Becoming Human

MAY 15, 2023

Note : Now, Start joining Data Science communities on social media platforms. These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

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. Bivariate EDA Contrary to intuition, Kilometers_Driven does not seem to have a relationship with the price.

Python 52

Python EDA Exploratory Data Analysis Data Analysis 52

Pickl AI

FEBRUARY 12, 2024

Data Science interviews are pivotal moments in the career trajectory of any aspiring data scientist. Having the knowledge about the data science interview questions will help you crack the interview. Clustering algorithms such as K-means and hierarchical clustering are examples of unsupervised learning techniques.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

AWS Machine Learning Blog

MAY 30, 2023

For ML model development, the size of a SageMaker notebook instance depends on the amount of data you need to load in-memory for meaningful exploratory data analyses (EDA) and the amount of computation required. We recommend starting small with general-purpose instances (such as T or M families) and scaling up as needed.

AWS 92

AWS ML ML EDA 92

Pickl AI

SEPTEMBER 12, 2024

Data Science is the art and science of extracting valuable information from data. It encompasses data collection, cleaning, analysis, and interpretation to uncover patterns, trends, and insights that can drive decision-making and innovation.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Snorkel AI

AUGUST 9, 2023

From there, we used Snorkel Flow to help identify and correct the model’s error modes in a data-centric development process. We corrected these via prompt where possible and then later via additional labeled data for fine-tuning. Built-in tools for EDA (filtering, sorting, clustering, tagging, etc.)

EDA 52

EDA AI AI Data Scientist 52

Heartbeat

JANUARY 25, 2023

Then they use these patterns to understand the public’s behavior and predict the election results, thus making more informed political strategies based on population clusters. Now you need to perform some EDA and cleaning on the data after loading it into the notebook. We pay our contributors, and we don’t sell ads.

Python 52

Python Deep Learning Deep Learning ML 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. What motivated you to participate? :

Natural Language Processing 130

Natural Language Processing Clustering Data Science Data Analysis 130

The MLOps Blog

DECEMBER 28, 2022

Data scientists frame the business problem and the objective into a statistical solution and start with the very first step of data exploration. EDA, as it is popularly called, is the pivotal phase of the project where discoveries are made. Approvals from stakeholders ML projects are inherently iterative by nature.

ML 78

ML ML Data Scientist Machine Learning 78