Towards AI

AUGUST 16, 2023

We can define an AI Engineering Process or AI Process (AIP) which can be used to solve almost any AI problem [5][6][7][9]: Define the problem: This step includes the following tasks: defining the scope, value definition, timelines, governance, and resources associated with the deliverable.

AI 96

AI AI Machine Learning Machine Learning 96

DrivenData Labs

APRIL 10, 2024

Summary of approach: In the end I managed to create two submissions, both employing an ensemble of models trained across all 10-fold cross-validation (CV) splits, achieving a private leaderboard (LB) score of 0.7318. I'd definitely would try more models pre-trained on remote sensing data.

Deep Learning 130

Deep Learning Deep Learning Machine Learning Machine Learning 130

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. The data is in good shape.

Python 52

Python AWS Exploratory Data Analysis Machine Learning 52

Pickl AI

FEBRUARY 22, 2024

The dedicated Statistics module focussing on Exploratory Data Analysis, Probability Theory, and Inferential Statistics. Free Online Statistics Course Educba 1+ video hours It features an extensive curriculum presented through high-definition video tutorials. There are live sessions with industry experts.

Data Science 52

Data Science Data Analysis Data Analysis Hypothesis Testing 52

Pickl AI

MARCH 26, 2024

Definition of KNN Algorithm K Nearest Neighbors (KNN) is a simple yet powerful machine learning algorithm for classification and regression tasks. Experimentation and cross-validation help determine the dataset’s optimal ‘K’ value. Unlock Your Data Science Career with Pickl.AI

K-nearest Neighbors 52

K-nearest Neighbors Machine Learning Machine Learning Algorithm 52

PyImageSearch

JANUARY 23, 2023

Firstly, we have the definition of the training set, which is refers to the training sample , which has features and labels. Applying XGBoost to Our Dataset Next, we will do some exploratory data analysis and prepare the data for feeding the model. Before we begin, just a few points.

Deep Learning 109

Deep Learning Deep Learning Algorithm Decision Trees 109

Pickl AI

AUGUST 29, 2023

The process of statistical modelling involves the following steps: Problem Definition: Here, you clearly define the research question first that you want to address using statistical modeling. Data Collection: Based on the question or problem identified, you need to collect data that represents the problem that you are studying.

Data Scientist 52

Data Scientist Clustering Data Analysis Data Analysis 52