Pickl AI

JULY 12, 2024

Jupyter notebooks allow you to create and share live code, equations, visualisations, and narrative text documents. Jupyter notebooks are widely used in AI for prototyping, data visualisation, and collaborative work. Their interactive nature makes them suitable for experimenting with AI algorithms and analysing data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

MARCH 26, 2024

Here are some notable applications where KNN shines: Classification Tasks Image Recognition: KNN is adept at classifying images into different categories, making it invaluable in applications like facial recognition, object detection, and medical image analysis. Unlock Your Data Science Career with Pickl.AI

K-nearest Neighbors 52

K-nearest Neighbors Machine Learning Machine Learning Algorithm 52

Pickl AI

OCTOBER 15, 2024

Summary: Statistical Modeling is essential for Data Analysis, helping organisations predict outcomes and understand relationships between variables. Introduction Statistical Modeling is crucial for analysing data, identifying patterns, and making informed decisions.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 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

DECEMBER 16, 2024

Documenting Objectives: Create a comprehensive document outlining the project scope, goals, and success criteria to ensure all parties are aligned. Making Data Stationary: Many forecasting models assume stationarity. Split the Data: Divide your dataset into training, validation, and testing subsets to ensure robust evaluation.

AI 52

AI AI Machine Learning Machine Learning 52

Mlearning.ai

MARCH 15, 2023

Data storage : Store the data in a Snowflake data warehouse by creating a data pipe between AWS and Snowflake. Data Extraction, Preprocessing & EDA : Extract & Pre-process the data using Python and perform basic Exploratory Data Analysis. Please refer to this documentation link.

Python 52

Python AWS Exploratory Data Analysis EDA 52

Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

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

Pickl AI

DECEMBER 10, 2024

Although it disregards word order, it offers a simple and efficient way to analyse textual data. TF-IDF (Term Frequency-Inverse Document Frequency) TF-IDF builds on BoW by emphasising rare and informative words while minimising the weight of common ones. Adopt an Iterative Approach Feature extraction is rarely a one-time process.

Machine Learning 52

Machine Learning Machine Learning Algorithm Deep Learning 52

DagsHub

APRIL 21, 2024

Scikit-learn Scikit-learn is a machine learning library in Python that is majorly used for data mining and data analysis. It also provides tools for model evaluation , including cross-validation, hyperparameter tuning, and metrics such as accuracy, precision, recall, and F1-score.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Pickl AI

DECEMBER 12, 2024

Regular updates, detailed documentation, and widespread tutorials ensure that users have ample resources to troubleshoot and innovate. Monitor Overfitting : Use techniques like early stopping and cross-validation to avoid overfitting. This flexibility is a key reason why its favoured across diverse domains.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

The MLOps Blog

DECEMBER 7, 2022

With all of that, the model gets retrained with all the data and stored in the Sagemaker Model Registry. This is a relatively straightforward process that handles training with cross-validation, optimization, and, later on, full dataset training. After that, a chosen model gets deployed and used in the model pipeline.

ML 52

ML ML AWS ETL 52

Heartbeat

MAY 29, 2023

It is therefore important to carefully plan and execute data preparation tasks to ensure the best possible performance of the machine learning model. It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78