Introduction to Machine Learning and Scikit-Learn

We are on a mission to transform technologists into world-class experts, and business people into tech-savvy leaders.It's that simple!Starweaver delivers superlative, hands-on and practical professional development and education focused on several key domains:1. Data Science, including big data, machine learning, data visualization, data analytics...2. Cloud Computing, including Amazon Web Services, Microsoft Azure, Google Cloud Platform / Firebase, IoT, Platform as a Service, Infrastructure as a Services, Software as a Service...3. Full Stack, including from front end (customer or user-facing) to the back end (the "behind-the-scenes" technology such as databases and internal architecture) including http, CSS, JavaScript, MongoDB, NodeJS, Angular, React...4. Agility & Stability, including a broad group of frameworks and techniques involving Agile, Scrum, Kanban, TOGAF, ITIL, cybersecurity...5. Business domains, including a strong emphasis on banking, finance, securities, and insurance (e.g., derivatives, credit risk management, corporate finance, financial modelling...)...Our business is designed to boost your knowledge and skills so that you can apply what you gain immediately in your job, or that next great job you are looking to start. We address, largely, more advanced, or complex subjects and convert those into rational, understandable, and usable information you can employ right away. If you want to take a great leap forward in your career, we are here to make that happen.Our instructors are seasoned practitioners who have worked in the fields their cover and relate the subjects covered to real work situations you will encounter in your job. So, the concepts are real, the coverage is at the right level of depth, and the material is straightforward.Who trusts us with their training requirements?  The world's preeminent companies, organizations, and agencies.  Specifically?  Check out our website and you will see that these are the best of the best.

Franco D'Angelo

<p>his course provides an introduction to the Python programming language essential for data manipulation, statistical analysis, and modeling techniques required for machine learning and artificial intelligence.  In this course we will explore the wonderfully concise and expressive use of Python’s advanced module features and apply it in probability, statistical testing, signal processing, financial forecasting, and various other applications. This course covers mathematical operations with array data structures, optimization, Probability Density Function, interpolation, Fast Fourier Transform, basic signal processing and other high performance benefits using the core scientific packages NumPy, Scipy, SkLearn/Scikit learn and Matplotlib. Students will gain a deep understanding and problem solving experience with these powerful platforms when dealing with engineering and scientific problems related to Machine Learning and Artificial Intelligence. The course will teach practical aspects of python for data wrangling needed for ML and AI applications so that the students will be able to apply lessons to solve problems using machine learning in their own careers and fields. The course uses examples to guide you through foundational concepts, often employing live algorithms to facilitate visual understanding. Pseudocode will be provided for most of the algorithms covered. You are encouraged to use the pseudocode as a reference to create your own programs in Python. The class has in-class quizzes to gauge learning and group activities including discussion. Homework assignments involving programming in Python are designed for in-depth practice.</p>

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Introduction to Machine Learning and Scikit-Learn

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Introduction to Machine Learning and Scikit-Learn

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