Search Constraints
Number of results to display per page
Results for:
Search Results
-
Others
Welcome! Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Fortunately an experienced programmer in any programming language (whatever it may be) can pick up Python very quickly. It's also easy for beginners to use and learn, so jump in!
- Course related:
- EIE3343 Computer System Principles
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
-
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, Data Science and Artificial Intelligence
- 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, Data Science and Artificial Intelligence
- 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, Data Science and Artificial Intelligence
- Keywords:
- SQL (Computer program language)
- Resource Type:
- Others
-
Others
Our calculator allows you to check your solutions to calculus exercises. It helps you practice by showing you the full working (step by step integration). All common integration techniques and even special functions are supported. The Integral Calculator supports definite and indefinite integrals (antiderivatives) as well as integrating functions with many variables. You can also check your answers! Interactive graphs/plots help visualize and better understand the functions.
- Course related:
- AMA1120 Basic Mathematics II - Calculas and Linear Algebra
- Subjects:
- Mathematics and Statistics
- Keywords:
- Calculus Integral
- 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, Data Science and Artificial Intelligence
- Keywords:
- Computer software -- Development Software engineering Git (Computer file)
- Resource Type:
- Others
-
Others
Math explained in easy language, plus puzzles, games, worksheets and an illustrated dictionary.
- Course related:
- AMA1120 Basic Mathematics II – Calculus and Linear Algebra and AMA1110 Basic Mathematics I – Calculus and Probability & Statistics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Mathematics
- 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, Data Science and Artificial Intelligence
- Keywords:
- Web site development Web publishing 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, Data Science and Artificial Intelligence
- 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, Data Science and Artificial Intelligence
- Keywords:
- Big data Data mining Machine learning
- Resource Type:
- MOOC