United States
United States
55375AC Fundamentals of Machine Learning course is an introductory course designed to provide a comprehensive overview of the tools, techniques, and algorithms used to solve the various tasks that arise when dealing with large data sets. The course takes an in-depth look at methods and models used to extract intelligence from data, as well as how to interpret the results of these models. The objective of the course is to provide a strong foundation in machine learning fundamentals and to give students the necessary background and preparation to evaluate, interpret, and apply modern machine learning algorithms.
Students enrolled in the course learn the basics of supervised and unsupervised learning algorithms, such as decision trees, support vector machines, and neural networks. They also become familiar with sampling, data pre-processing, feature extraction and selection, and validation. The course also covers cluster analysis, classification, regression, deep learning, and more.
This is a Rare Course and it can be take up to 3 weeks to arrange the training.
Get 1on-1 session with our expert trainers at a date & time of your convenience.
Flexible Dates
Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.
4-Hour Sessions
Training never been so convenient- attend training sessions 4-hour long for easy learning.
Destination Training
Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.| Live Online Training (Duration : 40 Hours) Fee On Request | |||
|---|---|---|---|
|
|||
The prerequisites for 55375AC Fundamentals of Machine Learning Training are:
* Knowledge of basic statistics
* Programming experience with Java, Python or another programming language
* Familiarity with databases and SQL
* Experience with data wrangling and data analysis
* A basic knowledge of linear algebra, probability and calculus
* Familiarity with Machine Learning concepts and terminology
* Knowledge of the cloud and cloud services such as AWS would be beneficial but is not required.
The target audience for 55375AC: Fundamentals of Machine Learning training is any individual with a technical background who wants to gain a further understanding of the fundamentals of machine learning
It is ideal for software developers, data scientists, AI researchers, and other professionals who may already have an understanding of the basic concepts but want to gain a more comprehensive understanding of how to apply machine learning principles and processes in their work
This training will introduce them to different types of supervised and unsupervised algorithms, and teach them how to develop and implement machine learning-powered applications
Learners will gain practical skills to help them design data engineering pipelines, select and process data, build and deploy models, and improve performance of machine learning models and projects
1. Understand principles and best practices of machine learning: Learn the fundamentals of machine learning, including how to build and design better algorithms, data prep and preprocessing, and the fundamentals of deep learning and neural networks.
2. Identify the right application for machine learning: Gain an understanding of common use cases of machine learning and when to use ML vs traditional software solutions or new models.
3. Work with different kinds of data: Work with structured and unstructured data, and use techniques such as supervised and unsupervised learning.
4. Implement machine learning algorithms: Learn how to code and implement various ML algorithms, such as K-means Clustering and linear regression.
5. Evaluate performance: Understand the criteria for evaluating ML models, such as accuracy, precision, recall, and more.
6. Understand ethical considerations: Gain an understanding of the ethical considerations in machine learning, such as privacy and fairness.
