Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Mlearning.ai

MARCH 15, 2023

Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit — Part 2 of 3 A comprehensive guide to develop machine learning applications from start to finish. Data Extraction, Preprocessing & EDA : Extract & Pre-process the data using Python and perform basic Exploratory Data Analysis.

Python 52

Python AWS Exploratory Data Analysis Machine Learning 52

Towards AI

JULY 19, 2023

Please refer to Part 1– to understand what is Sales Prediction/Forecasting, the Basic concepts of Time series modeling, and EDA I’m working on Part 3 where I will be implementing Deep Learning and Part 4 where I will be implementing a supervised ML model. This is part 2, and you will learn how to do sales prediction using Time Series.

Cross Validation 98

Cross Validation Clustering EDA Data Preparation 98

Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. What is cross-validation, and why is it used in Machine Learning? Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Ocean Protocol

FEBRUARY 1, 2024

Challenge Overview Objective : Building upon the insights gained from Exploratory Data Analysis (EDA), participants in this data science competition will venture into hands-on, real-world artificial intelligence (AI) & machine learning (ML). It’s also a good practice to perform cross-validation to assess the robustness of your model.

Exploratory Data Analysis 52

Exploratory Data Analysis Data Science Cross Validation Machine Learning 52

Pickl AI

SEPTEMBER 18, 2024

Step 2: Exploratory Data Analysis (EDA): Before running Regression Analysis, it’s essential to perform EDA to visualise data distributions and identify any outliers or patterns that may influence results. R, Python, SPSS) to estimate the parameters of your chosen model using methods like Ordinary Least Squares (OLS).

EDA 52

EDA Exploratory Data Analysis Hypothesis Testing Cross Validation 52

Pickl AI

SEPTEMBER 12, 2024

Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset. Exploratory Data Analysis (EDA): Analysing and visualising data to discover patterns, identify anomalies, and test hypotheses.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52