Codefinity. Project - Clustering Demystified

Project Clustering Demystified to track Foundations of Machine Learning.

In this project, we are going to understand what a cluster is and how to use it in Python.

Author: Edoardo Cantagallo

Clustering Demystified

 

Codefinity. Course Cluster Analysis.

Course Classification with Python of track Foundations of Machine Learning.

Clustering is one of the fundamental machine learning techniques that allows you to solve many complex problems in real life: market segmentation, anomaly detection, dimensionality reduction, revealing hidden patterns, etc.

Author: Ruslan Shudra

Cluster Analysis

 

Codefinity. Project - Identifying Spam Emails

Project Identifying Spam Emails to track Foundations of Machine Learning.

In this project, we are going to classify spam emails according to their content.

Author: Edoardo Cantagallo

Identifying Spam Emails

Codefinity. Course Classification with Python.

Course Classification with Python of track Foundations of Machine Learning.

In machine learning, classification is used in predictive modeling to assign input data with a class label. 

• k-NN Classifier
• Logistic Regression
• Decision Tree 
• Random Forest
• Comparing Models
  

 Author: Volodymyr Romanovych, Sofiia Piustonen

Classification with Python

 

Codefinity. Course Linear Regression with Python.

Course Linear Regression with Python of track Foundations of Machine Learning.

Linear Regression is a crucial concept in predictive analytics. It is widely used by data scientists, data analytics, and statisticians as it is easy to build and interpret but powerful enough for many tasks.

Author: Volodymyr Romanovych

• Simple Linear Regression 
• Multiple Linear Regression
• Polynomial Regression
• Choosing The Best Model

Linear Regression with Python

Codefinity. Mastered all the "Python Data Analysis and Visualization" specialization courses.

Track curriculum encompasses a collection of pivotal courses that provide foundational knowledge and skills essential for a successful journey in the field of data science. 

These courses encompass the comprehensive study of key concepts, tools, and methodologies integral to the realm of data analysis and modeling. 

By delving into courses centered around numpy, pandas, statistics, probability theory, as well as mathematics tailored for data analysis and modeling, learners are equipped with a well-rounded toolkit to seamlessly navigate the intricacies of data-driven exploration, manipulation, and inference.

6 courses 

Syllabus

1. Ultimate NumPy
2. Pandas First Steps
3. Advanced Techniques in pandas
4. Mathematics for Data Analysis and Modeling
5. Probability Theory Basics
6. Ultimate Visualization with Python
   

Python Data Analysis and Visualization

Codefinity. Ultimate Visualization with Python

Course Ultimate Visualization with Python of track Python Data Analysis and Visualization.

Data is everywhere around us, and making sense of it is extremely important. 

Visualization helps us deal with data by finding certain patterns and insights in it. 

We will develop a solid foundation of data visualization using Python and its libraries, such as matplotlib and seaborn, to get as much information from data as possible in a neat and concise way. Without further ado, let's dive in!

Author: Kyryl Sidak

 

Ultimate Visualization with Python

 

Codefinity. Ultimate NumPy.

Course Ultimate NumPy of track Python Data Analysis and Visualization.

Unlock the full potential of Python's most essential library for numerical computing, NumPy. 

This comprehensive course is designed to take you from a beginner's understanding to an advanced level of proficiency in NumPy. 

Whether you're a data scientist, engineer, researcher, or developer, mastering NumPy is essential for efficient data manipulation, scientific computing, and machine learning.

Author: Kyryl Sidak

Ultimate NumPy

 

"Kaggle" від Google "ml-competition-2024-for-ukrainian"

☀️ Перше моє змагання 📈 на "Kaggle" від Google "ml-competition-2024-for-ukrainian".

Приємно затягнуло 👨‍🎓, хоч і не потрапляю до 🏆призових місць top 50, і не претендую навіть на ґуґл ☕ чашку, хоча я вже отримав її за інше завдання 😃

Зареєстровані учасники, які увійдуть до ТОП-50 переможців у Kaggle-змаганні, отримають нагороди.

На сьогодні (за 4 доби до фінішу) 🔝зайняв 62 місце (піднявся з 87), і напевно вже вище не зможу стати, а тільки нище 😃. Але відновив деякі знання використовуючи записи з домашніх завдань курсів Data science в GoIT - start your career in IT : https://github.com/lexxai/goit_python_data_sciense_homework .