Dataconomy

JULY 28, 2023

Data preprocessing is a fundamental and essential step in the field of sentiment analysis, a prominent branch of natural language processing (NLP). Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Pickl AI

JULY 20, 2023

5. Text Analytics and Natural Language Processing (NLP) Projects: These projects involve analyzing unstructured text data, such as customer reviews, social media posts, emails, and news articles. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data.

Analytics 40

Analytics Analytics Big Data Big Data 40

Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). We will explore how to better understand the data that these models are trained on, and how to evaluate and optimize them for real-world use. This process ensures that the dataset is of high quality and suitable for machine learning.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

Pickl AI

DECEMBER 16, 2024

Long Short-Term Memory (LSTM) A type of recurrent neural network (RNN) designed to learn long-term dependencies in sequential data. Facebook Prophet A user-friendly tool that automatically detects seasonality and trends in time series data. Cleaning Data: Address any missing values or outliers that could skew results.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Analysis: This step involves applying statistical and Machine Learning techniques to analyse the cleaned data and uncover patterns, trends, and relationships.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52