Journey into Data Science with PythonDeep Dive into Numpy and Pandas with Housing Data

Intended for those interested in Machine Learning, this advanced course delves deeper into the extensive functionalities of Numpy and Pandas. The course covers complex operations, large-scale data manipulation, and cross-disciplinary applications.

Exploring the California Housing Dataset

Enhance the DataFrame with a New Population-Household Value Feature

Combining, Normalizing Features and Computing Weighted Sum with Numpy

Normalizing Matrix to [0, 1] Range

Fixing the Image Pixels Normalization and Weights Calculation

Normalization and Transposition of a Matrix

Mastering Advanced Matrix Operations with Numpy: Write from Scratch

Calculating Median Income by Room per Household

Grouping Data by Average Rooms Categories

Average Bedrooms Per Unit vs. Max Income: Debug and Fix

Calculate Average Population by Room Size Categories

Analyzing Average Bedrooms Across Different Age Categories in Housing Data

Speed Comparison: Python's Sum vs. Numpy's Sum

Memory Optimization: Compute and Display Percentage of Memory Saved

Optimizing Memory Usage through Data Type Conversions

Optimizing DataFrame Memory Usage by Converting Data Types

Optimizing Memory Usage for Large Datasets with Python, Numpy and Pandas

Sorting Gene Dataset by Popularity in Social Networks

Exploring Lowercase DNA Sequences in Bioinformatics Data

Exploring Bioinformatic Data and Filtering Astronomical Data

Manipulating Bioinformatics and Astronomical Data with Python, Pandas, and Numpy