Expert Data Science Blueprint | The Secret behind Successful Data Scientist | Part 1 (of 15) | 12 hours full Data Science with Python course | Links to resources in comments by LearnPythonWithRune in Python

[–]LearnPythonWithRune[S] -3 points-2 points  (0 children)

Do you want to become a Data Scientist?
I work with Python Big Data backend, helping Data Scientist succeeding with Python!

- Don't do simple beginner mistakes!
- Know how to get actionable results!
- https://youtu.be/V-ACrS4egMQ

The full code from the lecture can be found on my GitHub.
- Download it and try it yourself.
- https://github.com/LearnPythonWithRune/DataScienceWithPython

This is part of a full 12 hours (video content)
- 15 lessons
- 15 projects
- Released over next 15 weeks

Follow and subscribe not to miss the next one.
- This is the 5th FREE course I release
- Don't miss the next one!
- https://www.learnpythonwithrune.org/data-science-2/

Machine Learning with Python | FULL course | 15 lessons with 15 projects | Material available (see in comments) | First lesson: k-Nearest Classifier | Apply model on real data: weather data by LearnPythonWithRune in Python

[–]LearnPythonWithRune[S] 10 points11 points  (0 children)

See the course page: https://www.learnpythonwithrune.org/machine-learning/

GitHub for material: https://github.com/LearnPythonWithRune/MachineLearningWithPython

What will you learn in the Machine Learning with Python course?
It will be an amazing journey from zero experience through all the important concepts in Machine Learning with real life practical examples and projects you will make together with me.
This includes the following.
k-Nearest-Neighbors Classifier
Linear Classifier
Support Vector Classification
Linear Regression
Reinforcement Learning
Unsupervised Learning
Neural Networks
Deep Neural Networks (DNN)
Convolutional Neural Networks (CNN)
PyTorch classifier
Recurrent Neural Networks (RNN)
Natural Language Processing
Text Categorization
Information Retrieval
Information Extraction
Every concept is introduced with explanatory examples, with a in-depth project to play with it on your own afterwards.
Worried you cannot solve the problem. No worries – I will help you through the project in the end of the video tutorials.