Data Science in Practice: Case Study | AIML End-to-End Session 60
Ready to dive deep into the world of
Artificial Intelligence
Machine Learning (AIML)?
Welcome to Session 60 of our End-to-End AIML series! In this session, we focus on applying data science principles through a real-world case study. This hands-on session demonstrates how to tackle a data science problem from start to finish, integrating everything you've learned throughout the AIML series.
What You'll Learn:
Understanding the Problem: Learn how to define a data science problem, set objectives, and establish the scope of the project.
Data Collection and Exploration: Explore how to collect, clean, and preprocess data for analysis. We’ll dive into data wrangling, data cleaning, and handling missing data.
Exploratory Data Analysis (EDA): Use visualizations and statistical analysis to uncover patterns, trends, and correlations in the data.
Feature Engineering: Learn how to create new features that improve model performance, including handling categorical data, scaling, and normalizing data.
Model Building and Evaluation: Build and evaluate machine learning models, including regression, classification, or clustering models, based on the case study requirements.
Model Deployment: Discover how to take your model from a proof of concept to deployment, including model validation, testing, and performance monitoring.
Insights and Recommendations: Learn how to interpret the results of your model and provide actionable insights for stakeholders.
By the end of this session, you’ll understand how to apply data science techniques in a practical setting and take a project from data collection to actionable insights.
Subscribe to our channel for more hands-on data science and AIML tutorials, and don’t forget to like and share!
Seize this exclusive
opportunity to
accelerate your learning with Personalized
Live sessions tailored just for you!
Google Form Registration:
Secure your spot by filling out the Google Form below.
https://docs.google.com/forms/d/1dBgx...
#DataScience #AIML #CaseStudy #MachineLearning #DataAnalysis #EDA #FeatureEngineering #ModelBuilding #ModelDeployment #TechEducation #DataScienceInPractice #AIMLProjects #Coding #programming
@TwoMinutePapers
@3Blue1Brown
@sirajraval
@sentdex
@DeepMind
@lexfridman
@DataSchool
@TensorFlow
@PyTorch
@TheCodingTrain
@KrishNaik
@MachineLearningTV
@AIEngineering
@ArtificialIntelligence
@JeremyHoward
@TechWithTim
@GoogleAI
@AIandGames
@AIhub
@AIforAll
@HarvardInsights
@StanfordScholars
@MITOpenCourseWare
@UCBerkeleyOfficial
@OxfordAcademia
@CambridgeScholars
@YaleUniversity
@PrincetonPerspectives
@ColumbiaEducate
@CaltechDiscoveries
@UChicagoIntellect
@ImperialCollegeLondon
@ETHZurichKnowledge
@UniversityofTokyoOfficial
@UCLAInsights
@MichiganStateUniversity
@UniversityofToronto
@PekingUniversity
@NUSingapore
@ANUResearch
