Open Machine Learning Course

The “Open Machine Learning Course” delves into the practical applications of machine learning, emphasizing real-world scenarios and hands-on experience. It covers topics such as data augmentation, Python programming for web3 and blockchain, short-term memory in AI applications, and the importance of understanding and utilizing fast and slow aspects in Python development. Additionally, it explores the challenges of enterprise RAG implementations and the need for intelligent data processing beyond simple document retrieval. The course aims to equip learners with the skills needed to navigate complex machine learning tasks and build robust, efficient AI systems.

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Open Machine Learning Course. Topic 1. Exploratory Data Analysis with Pandas

With this article, we, OpenDataScience, launch an open Machine Learning course. This is not aimed at developing another comprehensive introductory course on machine learning or data analysis (so this…...

Open Machine Learning Course. Topic 9. Part 2. Predicting the future with Facebook Prophet

Open Machine Learning Course

Time series forecasting finds wide application in data analytics. These are only some of the conceivable predictions of future trends that might be useful: For another example, we can make a…

Open Machine Learning Course. Topic 10. Gradient Boosting

Open Machine Learning Course

So far, we’ve covered 9 topics from Exploratory Data Analysis to Time Series Analysis in Python. Today we are going to have a look at one of the most popular and practical machine learning…

Open Machine Learning Course. Topic 9. Part 1. Time series analysis in Python

Open Machine Learning Course

Let’s take a look at how to work with time series in Python, what methods and models we can use for prediction; what’s double and triple exponential smoothing; what to do if stationarity is not you…

Open Machine Learning Course. Topic 8. Vowpal Wabbit: Fast Learning with Gigabytes of Data

Open Machine Learning Course

This week, we’ll cover two reasons for Vowpal Wabbit’s exceptional training speed, namely, online learning and hashing trick, in both theory and practice. We will try it out with news, movie reviews…

Open Machine Learning Course. Topic 7. Unsupervised Learning: PCA and Clustering

Open Machine Learning Course

In this lesson, we will work with unsupervised learning methods such as Principal Component Analysis (PCA) and clustering. You will learn why and how we can reduce the dimensionality of the original…

Open Machine Learning Course. Topic 5. Bagging and Random Forest

Open Machine Learning Course

In the previous articles, you saw different classification algorithms as well as techniques for how to properly validate and evaluate the quality of your models. Now, suppose that you have chosen the…...

Open Machine Learning Course. Topic 6. Feature Engineering and Feature Selection

Open Machine Learning Course

In this course, we have already seen several key machine learning algorithms. However, before moving on to the more fancy ones, we’d like to take a small detour and talk about data preparation. The…

Open Machine Learning Course. Topic 4. Linear Classification and Regression

Open Machine Learning Course

Welcome to the 4-th week of our course! Now we will present our most important topic — linear models. If you have your data prepared and want to start training models, then you will most probably…

Open Machine Learning Course. Topic 2. Visual Data Analysis with Python

Open Machine Learning Course

In the field of Machine Learning, data visualization is not just making fancy graphics for reports; it is used extensively in day-to-day work for all phases of a project. To start with, visual…

Open Machine Learning Course. Topic 3. Classification, Decision Trees and k Nearest Neighbors

Open Machine Learning Course

A fractal tree. Source Hi! This is the third article in our series. Today we finally reach machine learning. This is going to be exciting! Article outline 1. Introduction 2. Decision Tree * How to Bui...