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Project Notebook Experiment: Exploring Data Science Techniques Welcome back to our Data Science Journey series! We' will dive into Day 3, where we'll be conducting a fascinating experiment using our project notebook. We'll be exploring various data science techniques, from data preprocessing to model building and evaluation. Here's what we'll cover: -Data Preprocessing: We'll start by cleaning and preparing our dataset for analysis. This involves handling missing values, encoding categorical variables, and scaling numerical features. -Exploratory Data Analysis (EDA): Next, we'll delve into the data to gain insights and understand the relationships between different variables. We'll create visualizations to identify patterns and trends within our dataset. -Feature Engineering: To improve the performance of our models, we'll engineer new features based on our domain knowledge and insights gained from EDA. -Model Building: Using popular machine learning algorithms such as decision trees, random forests, and gradient boosting, we'll train and evaluate several models to predict our target variable. -Model Evaluation: We'll assess the performance of each model using various evaluation metrics and techniques, ensuring that we choose the best model for our dataset. By the end of this experiment, we aim to gain a deeper understanding of our data and build predictive models that can provide valuable insights for our business or research objectives. Join us on this exciting journey as we explore the intricacies of data science through practical experimentation. Enrol now :-https://ineuron.ai/course/nlp-end-to-... Connect with us! Phone: +91 8071176111 Website: https://ineuron.ai/ Instagram: / official_ineuron.ai Discord: / discord YouTube: / @ineuronintelligence Hindi: / @ineurontechhindi Tech News: / @ineurontechnews DevHub: / @ineurondevhub DevOps : / @ineurondevops Non Tech : / @ineuronnontech Linkedin: / ineuron-ai Twitter: / ineuron_ai Quora: https://www.quora.com/profile/INeuron...