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Data Processing and Feature Engineering with MATLAB
by Adam Filion , Michael Reardon , Maria Gavilan-Alfonso , Brandon Armstrong , Heather Gorr , Erin Byrne , Brian Buechel , Isaac Bruss , Matt Rich , Nikola Trica , Cris LaPierre- 4.7
Approx. 18 hours to complete
Introduction to Module 1 Introduction to the Flights Dataset Introduction to Module 2: Organizing Your Data Introduction to Module 3: Cleaning Your Data Introduction to Module 4: Finding Features that Matter Introduction to Feature Engineering Introduction to Unsupervised Learning Introduction to Clustering Algorithms Introduction to Dimensionality Reduction and PCA Introduction to Module 5: Domain-Specific Feature Engineering...
Addressing Large Hadron Collider Challenges by Machine Learning
by Andrei Ustyuzhanin , Mikhail Hushchyn- 4.5
Approx. 24 hours to complete
The intensity of data flow is only going to be increased over the time. So the data processing techniques have to be quite sophisticated and unique. Write to us: coursera@hse. Introduction into particle physics for data scientists Introduction into the course...
Capstone: Autonomous Runway Detection for IoT
by Farhoud Hosseinpour , Juha Plosila- 0.0
Approx. 30 hours to complete
The students will learn how to motivate engineering decisions and how to choose implementations to make a system actually running. The students will also learn to evaluate the efficiency and the correctness of their system as well as real-world parameters such as energy consumption and cost. Introduction and methods Course introduction & Project overview...
Python and Machine Learning for Asset Management
by John Mulvey - Princeton University , Lionel Martellini, PhD- 3
Approx. 17 hours to complete
Welcome to the Python Machine-Learning for Investment management course Introduction to machine-learning First algorithms Introduction to module 2 - Basics of factor investing Introduction to module 3 -Machine learning techniques for efficient portfolio diversification Introduction to economic regimes Introduction to module 5 To be continued (3) Utilize powerful Python libraries to implement machine learning algorithms in case studies...
Digital Systems: From Logic Gates to Processors
by Elena Valderrama , Jean-Pierre Deschamps , Lluis TerĂ©s , Merce Rullan , JoaquĂn Saiz Alcaine , David Bañeres , Juan Antonio MartĂnez- 4.4
Approx. 29 hours to complete
Arithmetic components + Introduction to VHDL 2 (1outof2): Introduction to VHDL - Lexicon, syntax and structure 2 (2outof2): Introduction to VHDL - Lexicon, syntax and structure 3 (1outof2): Introduction to VHDL - Sequential sentences 3 (2outof2): Introduction to VHDL - Sequential sentences 4 (1outof2): Introduction to VHDL - Concurrent sentences 4 (2outof2): Introduction to VHDL - Concurrent sentences...
Python Searching & Sorting Algorithms - A Practical Approach
by Estefania Cassingena Navone- 4.5
6 hours on-demand video
Learn how to implement Searching and Sorting algorithms in Python. Be able to relate each line of code to the actual inner workings of the algorithms as they run. Learn how to implement these algorithms in Python. Be able to dive into more advanced algorithms with the solid foundation that this course provides....
$12.99
5 Courses - Master AWS, Analytics, Machine Learning, Bigdata
by Kaushik Vadali- 3.4
12 hours on-demand video
Bigdata and AWS, Hadoop on Amazon Elastic Map Reduce - EMR, Amazon EMR, Amazon EMR Architecutre, TensorFlow - Open source Machine Learning framework, Amazon SageMaker - TensorFlow Part 1 & 2, AWS Deep Learning AMIs, AWS Translate - Natual language translation, Amazon Polly - turn text to speech, Apache MXNet - Deep learning framework...
$12.99
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Introduction to Deep Learning & Neural Networks with Keras
by Alex Aklson- 4.7
Approx. 8 hours to complete
Looking to start a career in Deep Learning? Introduction to Neural Networks and Deep Learning Introduction to Deep Learning Introduction to Neural Networks and Deep Learning...
Design Thinking and Predictive Analytics for Data Products
by Julian McAuley , Ilkay Altintas- 4.5
Approx. 8 hours to complete
Introduction to Supervised Learning Introduction to Support Vector Machines Introduction to Training and Testing Where to Find Datasets...
Code Yourself! An Introduction to Programming
by Dr Areti Manataki , Inés Friss de Kereki- 4.7
Approx. 12 hours to complete
Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language. More importantly, it will introduce you to the fundamental principles of computing and it will help you think like a software engineer. Introduction to Scratch...