Machine Learning
Machine Learning Courses Online and Certifications
Are you ready to dive into the exciting world of machine learning? Edcroma’s machine learning course is designed for beginners and experienced learners alike, providing a comprehensive understanding of machine learning concepts and techniques that are transforming industries worldwide. Machine learning is at the forefront of technological innovation, influencing sectors such as healthcare, finance, marketing, and more.
Learn Data Science to analyze and interpret complex data sets.
What You Will Learn:
- Introduction to Machine Learning:
Understand the basics of machine learning, including types of learning (supervised, unsupervised, and reinforcement). Learn about the differences between traditional programming and machine learning, and how machines can learn from data. - Key Algorithms:
Explore popular algorithms such as linear regression, decision trees, random forests, and support vector machines. You’ll learn how these algorithms function and when to apply them in real-world scenarios.
Explore Artificial Intelligence for a deeper understanding of AI technologies.
Showing 1–12 of 273 results
A Quick Introduction to Machine Learning
Start your machine learning journey with this quick introduction. Learn the fundamental concepts and algorithms used in ML, including supervised and unsupervised learning, data preprocessing, and model evaluation techniques.
Accelerating Deep Learning with GPUs
Learn how to accelerate deep learning models using GPUs. Understand the importance of parallel processing and how to optimize model training times by leveraging the power of GPU computing for deep neural networks.
Advanced Deep Learning with Keras
Learn how to develop deep learning models with Keras.
Advanced Text Analytics: Topic Modeling and Named Entity Recognition
Learn how to use advanced topic modeling and named entity recognition (NER) for text analytics, covering the math and code behind topic modeling and NER algorithms (e.g., transformer-based) and how to integrate both in your workflows.
Analyze NFL Stats with Python Case Study
Use NFL team statistics to model game winners and discover the most important team-level stats
Analyze Taylor Swift Lyrics with Python Case Study
Use sentiment analysis and natural language processing to analyze Taylor Swift's lyrics.
Analyze Traffic Safety Data with Python Case Study
Create data visualizations of traffic data from the last two decades and model the relationship between smartphones and collision rates.
Anomaly Detection in Python
Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.
Apply Natural Language Processing with Python
Learn Python for Natural Language Processing, the field behind chatbots, search engines, and autocorrect.
Architecting Production-ready ML Models Using Google Cloud ML Engine
This course covers Cloud ML Engine, a powerful service that supports distributed training and evaluation for models built in TensorFlow, Scikit-learn and XGBoost.
ARIMA Models in Python
Learn about ARIMA models in Python and become an expert in time series analysis.
Automate Content Recommendation with Transformer Embeddings
Learn how to use transformer-based embeddings to automate content recommendations. Explore how deep learning models like BERT or GPT can be leveraged to enhance recommendation systems by understanding content and user preferences.
- Data Preprocessing:
Learn the importance of preparing data for analysis. This includes data cleaning, normalization, and feature selection, which are crucial steps before feeding data into a machine-learning model. - Hands-On Projects:
Apply your knowledge through real-world projects that demonstrate the power of machine learning. Work on case studies and projects that allow you to build and train models, analyze data, and interpret results.
Dive into Deep Learning to understand advanced neural network techniques.
- Tools and Technologies:
Learn to use programming languages like Python and libraries such as TensorFlow, Keras, and Scikit-learn. Familiarize yourself with these tools to implement machine learning algorithms effectively. - Model Evaluation and Improvement:
Understand how to evaluate the performance of your machine learning models using metrics such as accuracy, precision, recall, and F1 score. Learn techniques for improving model performance through hyperparameter tuning and cross-validation.
Why Choose This Course?
Our best machine learning course offers flexible learning options, allowing you to study at your own pace. With comprehensive content, practical examples, and expert guidance, you will be equipped with the skills needed for a career in this rapidly growing field. Whether you’re aiming for a career switch or looking to enhance your existing skills, this course is designed to meet your goals.
Explore Data Analytics to master the art of turning data into actionable insights.
Free Machine Learning Course:
At EdCroma, we believe in accessible education. That’s why we offer a free machine learning course that provides you with essential knowledge without any cost. You can start learning today and build a strong foundation in machine learning! The free course includes lectures, assignments, and community support to enhance your learning experience.
Learn about Neural Networks to understand advanced deep learning models.
Enroll Now!
Join our machine intelligence course and unlock your potential in the tech world. Sign up today to start your journey in machine learning and enhance your career opportunities! Whether you aim to become a data scientist, or machine learning engineer, or simply want to understand this fascinating field, EdCroma is your gateway to success.