mldlai-campos - Notebooks

Machine Learning With Python (IBM Data Science Specialization)

Simple Linear Regression

Polynomial Regression

Logistic Regression

Agglomerative or Hierarchical Clustering

Multiple Linear Regression

K-Nearest Neighbors (KNN)

Support Vector Machines (SVM)

Density Based Clustering (DBSCN)

Non-Linear Regression

Decision Trees

K-Means

Content-Based Recommendation System

Collaborative Filtering Recommendation System

Data Analysis with Python

Data Wrangling

Exploratory Data Analysis

Model Development

Data Analysis with Python

Model Evaluation and Refinement

Area Plots, Histograms, and Bar Plots

Hierarchical Clustering Algorithm

Maps in Python

Pie Charts, Box Plots, Scatter Plots, and Bubble Plots

Waffle Charts, Word Clouds, and Regression Plots

K-Nearest Neighbors Algorithm

Linear Algebra for Machine Learning and Data Science (DeepLearning.ai)

Introduction to Python Matrices and NumPy

Solving Linear Systems: 2 Variables

Solving Linear Systems: 3 Variables

System of Linear Equations

Matrix Multiplication

Linear Transformations

Vector Operations: Scalar Multiplication, Sum and Dot Product of Vectors

Single Perceptron Neural Networks for Linear Regression

Eigenvalues and Eigenvectors

Machine Learning Scientist with Python (DataCamp)

Supervised Learning with Scikit-Learn

Model Validation in Python

Building Deep Learning Models with TensorFlow (IBM AI Engineering)

Introduction to Deep Learning & Neural Networks with Keras (IBM AI Engineering)

Artificial Neural Networks - Forward Propagation

Classification Models with Keras

Regression Models with Keras

Convolutional Neural Networks with Keras

Natural Language Processing with Classification and Vector Spaces (DeepLearning.AI)

Logistic Regression Model

Word Frequencies

Preprocessing

Logistic Regression Assignment

Visualizing Naive Bayes

Naive Bayes Assignment

Linear Algebra

Word Vectors with PCA

Manipulating Word Embeddings

Word Vector Assignments

Vector Manipulation in Python

Word Translation Assignment

Hash Functions and Multiplanes

Algorithms for Searching, Sorting, and Indexing (University of Colorado Boulder)

Binary Search

MergeSort

Assignment 1 Algorithms

Spark and Python for Big Data with PySpark (Udemy)

Dataframe Basics

Dataframe Basic Operations

Dates and Timestamps

GroupBy and Aggregate Functions

Missing Data

SpaceX (IBM Data Science Specialization)

This project follows the IBM Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting results to stakeholders.

The project predicts if the first stage of the SpaceX Falcon 9 rocket will land successfully.

SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage.

Therefore to determine the cost of a launch, we have to accurately predict the likelihood of the first stage rocket landing successfully.

Project folder

Drug Classification (IBM Data Science Specialization)

Drug Classification

In this project, you assume the role of a medical researcher building a classification model to find out which drug might be appropriate for a future patient based on a study where data was collected and patients responded to one of the following 5 medications: Drug A, Drug B, Drug c, Drug x, and Drug y.

Decision Tree Algorithm