Search Constraints
Number of results to display per page
Results for:
Search Results
-
Others
Scikit Learn provide simple and efficient tools for predictive data analysis. Assessible to everybody, and reusable in various contexts. It built on NumPy, SciPy, and matplotlib. It is open sources, commercially usable under the BSD License.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
-
Video
This youtube playlist included the topic of deep learning for human language processing, linear algebra, deep reinforcement learning, generative adversarial network, deep learning theory, structured learning, and machine learning.
- Course related:
- LGT6801 Guided Study in Logistics I
- Subjects:
- Computing
- Keywords:
- Machine learning Natural language processing (Computer science)
- Resource Type:
- Video
-
Others
SQL is a standard language for storing, manipulating and retrieving data in databases.Our SQL tutorial will teach you how to use SQL in: MySQL, SQL Server, MS Access, Oracle, Sybase, Informix, Postgres, and other database systems.
- Course related:
- COMP5112 Data Structures and Database Systems
- Subjects:
- Computing
- Keywords:
- SQL (Computer program language)
- Resource Type:
- Others
-
Others
GitHub is a development platform inspired by the way you work. From open source to business, you can host and review code, manage projects, and build software alongside 50 million developers. GitHub brings teams together to work through problems, move ideas forward, and learn from each other along the way. You can write better code, manage your chaos, and find the right tools in GitHub.
- Course related:
- EIE6811 Guided Study in Electronic and Information Engineering I/II/III and EE4006A Individual Project
- Subjects:
- Computing
- Keywords:
- Computer software -- Development Git (Computer file) Software engineering
- Resource Type:
- Others
-
Others
W3Schools is optimized for learning, testing, and training. Examples might be simplified to improve reading and basic understanding. Tutorials, references, and examples are constantly reviewed to avoid errors, but we cannot warrant full correctness of all content.
- Subjects:
- Computing
- Keywords:
- Web publishing Web site development Web sites -- Design
- Resource Type:
- Others
-
Others
This Linux tutorial is divided into 13 sections. In general I recommend you work through them in order but if you've come here just to learn about a specific topic then feel free to just go straight to that one. You can now jump into section 1 and get started or keep reading below to learn a little more about this tutorial. 1.The Command Line - What is it, how does it work and how do I get to one. 2.Basic Navigation - An introduction to the Linux directory system and how to get around it. 3.More About Files - Find out some interesting characteristics of files and directories in a Linux environment. 4.Manual Pages - Learn how to make the most of the Linux commands you are learning. 5.File Manipulation - How to make, remove, rename, copy and move files and directories. 6.Vi Text Editor - Discover a powerful Linux based text editor. 7.Wildcards - Also referred to as globbing, this is a means to refer to several files in one go. 8.Permissions - Learn to identify and change the permissions of files and directories and what the consequences of these are. 9.Filters - An introduction to various commands that allow us to mangle data in interesting and useful ways. 10.Grep and Regular Expressions - Master a powerful pattern matching language that is useful for analysing and processing data. 11.Piping and Redirection - Join commands together in powerful combinations. 12.Process Management - See what is currently running on your Linux system and what state the system is in, learn how to kill programs that have hung and put jobs in the background. 13.Scripting - Be happy. Get the computer to do tedious and repetitive tasks for you. 14.Cheat Sheet - A quick reference for the main points covered in this tutorial.
- Subjects:
- Computing
- Keywords:
- Linux Operating systems (Computers)
- Resource Type:
- Others
-
MOOC
Data science has critical applications across most industries, and is one of the most in-demand careers in computer science. Data scientists are the detectives of the big data era, responsible for unearthing valuable data insights through analysis of massive datasets. And just like a detective is responsible for finding clues, interpreting them, and ultimately arguing their case in court, the field of data science encompasses the entire data life cycle. That starts with capturing lots of raw data using data collection techniques, and then building and maintaining data pipelines and data warehouses that efficiently “clean” the data and make it accessible for analysis at scale. This data infrastructure allows data scientists to efficiently process datasets using data mining and data modeling skills, as well as analyze these outputs with sophisticated techniques like predictive analysis and qualitative analysis. Finally, these findings must be presented using data visualization and data reporting skills to help business decision makers. Depending on the size of the company, data scientists may be responsible for this entire data life cycle, or they might specialize in a particular portion of the life cycle as part of a larger data science team
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Big data
- Resource Type:
- MOOC
-
MOOC
The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.
- Course related:
- COMP4431 Artificial Intelligence
- Subjects:
- Computing
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
-
MOOC
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.
- Course related:
- AMA564 Deep Learning
- Subjects:
- Computing
- Keywords:
- Machine learning Neural networks (Computer science) Artificial intelligence
- Resource Type:
- MOOC
-
Courseware
In this course, you will walk away with an up-to-date examination of the maturing FinTech industry and an understanding of the technologies set to shape the future of finance. Insight into who is currently adopting and driving financial technology innovation and the potential for partnerships between incumbents, start-ups and investors. The ability to critically assess the future of the financial services industry, through exploring complex real-world problems and how FinTech can be used to find solutions.A strategic framework to apply within your own role, and the opportunity to share this with like-minded professionals at an additional conference week.
- Course related:
- COMP4142 E-Payment and Cryptocurrency and COMP5521 Distributed Ledger Technology
- Subjects:
- Finance and Computing
- Keywords:
- Financial services industry -- Technological innovations Finance -- Technological innovations
- Resource Type:
- Courseware