Tech Journal

This notebook is an exercise in the Introduction to Machine Learning course. You can reference the tutorial at this link. Recap Here’s the code you’ve written so far. # Code you have previously used to load data import pandas as pd from sklearn.metrics import mean_absolute_error from sklearn.model_selection imp... Read More

Part I The Fundamentals of Machine Learning Chapter 1. The Machine Learning Landscape In this chapter I will start by clarifying what machine learning is and why you may want to use it. Then, befroe we set out to explore the machine learning continent, we will take a look at the map and elarn about the main region... Read More

Chapter 1. Exploratory Data Analysis This chapter focuses on the first step in any data science project: exploring the data. Exploratory data analysis, or EDA, is a comparatively new area of statistics. Classical statistics focused almost exclusively on inference, a sometimes complex set of procedures for drawing c... Read More

This notebook is an exercise in the Introduction to Machine Learning course. You can reference the tutorial at this link. Recap You’ve built your first model, and now it’s time to optimize the size of the tree to make better predictions. Run this cell to set up your coding environment where the previous step lef... Read More

📌 Phase 1.3 - Enhance API Response with Data Formatting & Insights 1. Objectives ✅ Goal Enhance API responses by providing structured, insightful, and easily interpretable data for better decision-making. 🎯 Key Tasks Refine API Response Structure: Enhance response structure with clear formatting. Inclu... Read More