Codefinity. Mastered all the "Foundations of Machine Learning" specialization courses.

The track provides an introduction to the essential concepts and techniques in the field of machine learning. 

This comprehensive learning journey covers various crucial topics, including the utilization of scikit-learn library for machine learning initiation, the application of Linear Regression for predictive modeling, exploration of Classification methods for categorizing data, and the study of Clustering algorithms to discover inherent patterns within datasets. 

By engaging with this track, learners will acquire a solid understanding of fundamental machine learning principles, enabling them to build predictive and analytical models across diverse domains.

8 courses

Syllabus

1. ML Introduction with scikit-learn
   
2. Linear Regression with Python
3. Classification with Python
4. Identifying Spam Emails (Project)
5. Cluster Analysis
6. Clustering Demystified (Project)
7. Ensemble Learning
8. Logistic Regression Mastering (Project)
   

Foundations of Machine Learning

 

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 .

Codefinity. ML Introduction with scikit-learn.

Course. ML Introduction with scikit-learn of track Foundations of Machine Learning.

Machine Learning is now used everywhere. Want to learn it yourself? 

This course is an introduction to the world of Machine learning for you to learn basic concepts, work with Scikit-learn – the most popular library for ML and build your first Machine Learning project. 

This course is intended for students with a basic knowledge of Python, Pandas, and NumPy.

Author: Volodymyr Romanovych

 

ML Introduction with scikit-learn.

Codefinty. Project - Recognizing Handwritten Digits.

Postgraduate of completed track - Python. Preparation for Data Science. Consists of 9 courses.

• Recognizing Handwritten Digits.
  In this project, our primary objective will be to delve into the identification of handwritten digits through the application of machine learning algorithms. This endeavor aims to harness the power of machine learning to effectively interpret and understand handwritten digits, showcasing the potential of these algorithms in processing and analyzing complex visual information.
  

Recognizing Handwritten Digits

Codefinity. Successfully completed track - Python. Preparation for Data Science. Consists of 9 courses.

Track "Preparation for Data Science", 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. 

The curriculum's diverse content ensures a robust understanding of critical elements in data science, cultivating a solid base for individuals venturing into this dynamic and ever-evolving domain.

Preparation for Data Science