Machine Learning Scientist mit Python

"Verbessern Sie Ihre Machine-Learning-Fähigkeiten mit scikit-learn in Python. Nutzen Sie reale Datensätze!"

Dive into agriculture using supervised machine learning and feature selection to aid farmers in crop cultivation and solve real-world problems.

Lernen Sie, wie Sie mit scikit-learn und scipy unbeschriftete Datensätze clustern, transformieren und visualisieren.

Arctic Penguin Exploration: Unraveling Clusters in the Icy Domain with K-means Clustering

In this course you will learn the details of linear classifiers like logistic regression and SVM.

In diesem Kurs lernen Sie, wie Sie baumbasierte Modelle und Ensembles für Regression und Klassifikation mit scikit-learn verwenden.

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Learn how to clean and prepare your data for machine learning!

This course focuses on feature engineering and machine learning for time series data.

Create new features to improve the performance of your Machine Learning models.

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Lerne grundlegende Techniken der Verarbeitung natürlicher Sprache mit Python und wende sie auf Textdaten an.

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

"Lernen Sie, Ihr erstes neuronales Netzwerk zu erstellen, Hyperparameter anzupassen und Probleme in PyTorch zu lösen."

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

Learn to process, transform, and manipulate images at your will.

Lernen Sie, verteiltes Datenmanagement und maschinelles Lernen in Spark mit dem PySpark-Paket umzusetzen.

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Learn how to approach and win competitions on Kaggle.