Machine Learning With Python Workshop by Tonex
The “Machine Learning With Python Workshop” is an intensive training program offered by Tonex, designed to equip participants with the essential knowledge and skills required to excel in the field of machine learning using Python. This workshop provides a comprehensive overview of machine learning concepts and hands-on experience in implementing machine learning algorithms using Python libraries.
Learning Objectives: Upon completion of the “Machine Learning With Python Workshop,” participants will:
- Learn the fundamentals of machine learning and its applications.
- Gain proficiency in Python programming for machine learning.
- Explore various machine learning algorithms and their real-world use cases.
- Develop the ability to preprocess data and perform feature engineering.
- Implement and evaluate machine learning models using Python’s popular libraries.
- Apply machine learning techniques to solve practical problems and make data-driven decisions.
Audience: This workshop is ideal for:
- Data Scientists and Analysts looking to expand their machine learning expertise.
- Software Developers interested in integrating machine learning into their applications.
- Business Analysts aiming to leverage machine learning for data-driven insights.
- Researchers and Academics seeking to enhance their knowledge of machine learning with Python.
- Anyone interested in a career in machine learning and artificial intelligence.
- Professionals in diverse industries seeking to stay ahead in the rapidly evolving field of technology.
Course Outline:
Introduction to Machine Learning
- Understanding machine learning concepts
- Types of machine learning (supervised, unsupervised, reinforcement)
- Machine learning workflow
- Python as a primary tool for machine learning
- Setting up Python and essential libraries
Data Preparation and Exploration
- Importing and cleaning data
- Exploratory data analysis
- Feature engineering
Python Fundamentals for Machine Learning
- Python syntax and data structures
- Working with libraries like NumPy and Pandas
- Data visualization with Matplotlib and Seaborn
- Data preprocessing and cleaning techniques
- Hands-on exercises in Python for data manipulation
Supervised Learning Algorithms
- Linear regression for regression tasks
- Logistic regression for classification problems
- Decision trees and random forests
- Support vector machines (SVM)
- Naive Bayes classifiers
- Model evaluation and validation techniques
Unsupervised Learning and Clustering
- K-means clustering
- Hierarchical clustering
- Principal Component Analysis (PCA)
- Dimensionality reduction techniques
- Evaluating clustering performance
- Practical clustering applications
Deep Learning with Neural Networks
- Introduction to artificial neural networks
- Building and training neural networks with TensorFlow and Keras
- Convolutional Neural Networks (CNNs) for image recognition
- Recurrent Neural Networks (RNNs) for sequential data
- Transfer learning and pre-trained models
- Deploying neural networks in real-world scenarios
Model Deployment and Case Studies
- Model deployment strategies
- Creating APIs for machine learning models
- Monitoring and maintaining deployed models
- Real-world case studies and use cases
- Ethical considerations in machine learning
- Future trends and emerging technologies in the field
This comprehensive “Machine Learning With Python Workshop” will provide participants with the knowledge and practical skills required to excel in the ever-evolving world of machine learning and artificial intelligence using Python.