DataKwery 的教程和研讨会
Building Machine Learning Pipelines in Python with scikit-learn - ML Workshop #6 of 6
2022年12月3日 –
Evaluating and Fine-Tuning Classification Models in Python with Scikit-learn - ML Workshop #5 of 6
2022年11月19日 –
Machine Learning Fundamentals with Python Workshop #5 aims to improve upon our initial logistic regression classification model.
Building Your First Classification Model in Python with Scikit-learn - ML Workshop #4 of 6
2022年10月1日 –
The 4th of 7 live workshops on Machine Learning in Python turns to classification models using Logistic Regression.
Evaluating and Fine-Tuning Regression Models in Python with Scikit-learn - ML Workshop #3 of 6
2022年9月3日 –
The third of 7 live workshops on Machine Learning in Python applies feature engineering steps to our original linear regression model. The result? Much more accurate predictions.
Feature Engineering Foundations in Python with Scikit-learn - ML Workshop #2 of 6
2022年8月6日 –
The second of 7 live workshops on Machine Learning in Python explores the basics of feature engineering and pipeline building.
Building Your First Regression Model in Python with Scikit-learn - ML Workshop #1 of 6
2022年7月2日 –
The first workshop covers building Machine Learning models in Python with Scikit-learn. We start with a focus on linear regression and discuss data preparation, model construction, and performance evaluation.
Data Science Career Tracks - What's the right path for you?
2022年6月3日 –
Data skills are in demand across all industries and job functions. This webinar will discuss the core data science career tracks of 2022, along with what specific skills are needed, what tools are used, and how much can you expect to get paid for typical roles, including Business Analyst, Data Analyst, Data Scientist, Data Engineer, Data Architect, and Chief Data Officer.
We'll also highlight free learning paths to take you from data novice to data professional in no time.
Should I learn Python or R?
2022年4月19日 –
To R, or to Python? This is the data science question of the day and top of mind for people breaking into the world of data science.
At this free webinar, we’ll discuss the pros and cons of each tool from a practical perspective and with specific use cases in mind. Though side-by-side live coding examples we’ll see just how much can be accomplished with these two amazing (and free) data science tools.