Who’s this for

Programmers, developers

 

Program Format

Online and masterclasses

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One-of-kind Machine Learning Training To Build Intelligent Applications

A dedicated Machine Learning specialization with special focus on practical case studies and hands-on experience in Prediction, Classification, Clustering, and Information Retrieval. This is your cue to learn and analyze complex datasets, develop adaptive systems, and create predictive applications.

  • tick_imagePractice and implement predictive, classification, clustering, and information retrieval algorithms across actual datasets.
  • tick_imageA hands-on approach in machine learning and mastering Python programming skills.
  • tick_imageParticipants will gain skills in analyzing extensive and complex datasets and crafting adaptable systems that continuously improve.

Your Gateway To A Future-proof Advanced Machine Learning Training Is Here

Participants in the course will delve into regularized linear regression models for prediction and feature selection, mastering the handling of extensive feature sets and navigating models of varying complexities while implementing optimization algorithms suitable for large datasets. The learning objectives encompass a comprehensive understanding of classification models, including binary and multiclass classification, logistic regression for large-scale classification, nonlinear models using decision trees, boosting techniques for enhanced performance, stochastic gradient ascent for scaling methods, and evaluating models using precision-recall metrics, all implemented in Python. By the end of the course, learners will be equipped to:

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Build document retrieval systems with k-nearest neighbours

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Identify text data similarity metrics

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Optimize k-nearest neighbour search using KD-trees

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Generate approximate nearest neighbours with locality-sensitive hashing

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Differentiate supervised and unsupervised learning tasks

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Cluster documents using k-means, parallelize k-means using MapReduce

Tools Covered

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Data Science & Machine Learning Courses Mentors

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Talk To Our Program Coordinator

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Specialized Advanced Machine learning Course Online For Futuristic Roles

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    Machine Learning Expert: Employ a range of machine learning tools and technologies to build statistical models leveraging vast business data resources.

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    Senior Data Scientist: Identify challenges, develop models based on collected data, and supervise a team of data scientists.

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    Applied Scientist: Create and refine machine learning models to enhance intelligence for organizational products and services.

 

Who Should Attend Our Machine Learning Bootcamp Program?

  • Data Scientists and Analysts
  • Software Engineers
  • Business Analysts
  • Programmers and Developers
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Client Testimonials

Trusted By The Best In The Business

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Frequently Asked Questions!

Here are answers to some of the most commonly asked questions by our clients.

1. What can I expect from StackRoute’s Advanced Machine Learning Program ? groupgroup

The Advanced Machine Learning Program from StackRoute has a comprehensive curriculum covering advanced topics in data science and machine learning, with a part-time option available for flexibility. The program emphasizes hands-on learning, enabling participants to apply their knowledge to real-world projects. Moreover, StackRoute's approach embraces full-stack thinking, empowering small teams with self-sufficient skills for digital transformations.

2. Do I need any prior knowledge for enrolling in Advanced Machine Learning Training?groupgroup

Prior experience in computer programming is recommended as most tasks within this Specialization are conducted using the Python programming language. The program targets data scientists and software developers aiming to enhance their expertise in data science and machine learning. However, it is also suitable for individuals with fundamental math and programming skills, as well as an interest in extracting insights from data.

3. Is Python mandatory for Advanced Machine Learning Course Online?groupgroup

Python is highly recommended for ML due to its simplicity, readability, and vast libraries. It offers tools like NumPy, Pandas, and Scikit-Learn essential for data manipulation and model building. While other languages like R and Java are used in ML, Python's popularity makes it a preferred choice.
4. How much Python do I need to know for machine learning?groupgroup
Basic Python knowledge (syntax, data types, control structures) is essential. Familiarity with libraries like NumPy (for numerical operations) and Pandas (for data manipulation) is crucial. Understanding functions, loops, and conditional statements is necessary for writing ML code. Advanced topics like object-oriented programming and decorators may be beneficial for complex ML projects.

Reach out to us!

Got a question about our programs? Interested in partnering with us? Got suggestions or just want to say hi? Contact us below:

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