Some important things that you are eager to have for the PhD journey
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- Literatures Daily
- Awesome Courses
- Conference Guideline
- General Tips
- Awesome AI and Data Science
- Things of Python
- Datasets
- Article writing
- Books and Cheatsheet
- Awesome Collections for PhD
- Thoughts in AI
- The top list of academic research databases
- Citation Management Tools
- List of Journals
- Bootcamp
- Machine Learning and Deep Learning
- Federate Learning
- Internet of Things
- Career Development
- 9 ways to survive in phd journey
- Rankings of computer science based on metrics of publish in top conference, very useful for finding sub-domain area and the top authors! |2023-07-17|
- Speed write for paper to generate original text for paper writing |2023-03-13|
- What's the different between Scopus and Web of Science?
- List of Web of Science Journals in Computer Science
- Between Python and Julia: A Comparative Analysis |2023-02-06|
- A.I. and education can go hand and hand, says Khan Academy’s Sal Khan |2023-02-10|
- The ChatGPT prompts any data scientist must use |Abhinaba Banerjee|2023-02-13|
- Not stuck in git |Brooke Jamieson|2023-02-13|
- Lazy predict tool with basic metrics of classsification and regression |2023-02-21|
- Scite, AI-powered for real citations to actually published papers |2023-02-23|
- Systematic Literature Review of Information Extraction From Textual Data: Recent Methods, Applications, Trends, and Challenges This study investigated and described the most contemporary methods for extracting information from textual data, emphasizing their benefits and shortcomings. |2023-02-23|.
- Applied Machine Learning Machine learning is a powerful tool for extracting insights from data and making predictions. Applied machine learning refers to the use of machine learning techniques to solve real-world problems. This can involve building models to predict customer behavior, identify fraud, or diagnose medical conditions, among other applications. In this article, we will discuss the steps involved in applied machine learning. |2023-03-05|
Topics | Sources | Introduction | Audience | Date |
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Interactive Canvas for DS | Einblick | Einblick is the fastest and most collaborative way to explore data, create predictions, and deploy data apps. | Anyone who likes visual operation on datasets | 2023-01-15 |
Awesome AI Tools | Futurepedia | The largest AI tools depository, daily update | Anyone who likes use AI tools to play | 2023-01-15 |
Advanced Statistics for Data Science | Coursera | Familiarize yourself with fundamental concepts in probability and statistics, data analysis and linear models for Data Science. | Fundamentals for data science | 2023-01-15 |
MathGPT | GPT | Use GPT3 to solve math problems, and get the code behind each solution! | For efficient math operations | 2023-01-15 |
Chatsonic | Chatsonic | Chrome extension, Use personalized avatars, Write factual real-time content, Share, edit, download conversations | may be an alternative of ChatGPT | 2023-02-05 |
All algorithms implemented in Python | The Algorithms | All algorithms implemented in Python, for education Implementations are for learning purposes only. They may be less efficient than the implementations in the Python standard library. Use them at your discretion. | Python coding | 2023-02-06 |
Teaching/learning Python 3 (3.5+) | Jerry Pussinen | This repository contains a collection of materials for teaching/learning Python 3 (3.5+). | Python learning for beginner and intermidate | 2023-02-06 |
DataScienceResources | jonathan-bower | The intended goal was to cover more than just the technical component of data science. I have tried to find topics that cover building data science teams, business practices, use-cases, product metrics and data science career paths. Hope this is helpful | Data science learner | 2023-02-06 |
awesome-datascience | Fatih Aktürk, Hüseyin Mert & Osman Ungur, Recep Erol. | An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start studying Data Science. Just follow the steps to answer the questions, "What is Data Science and what should I study to learn Data Science?" | Data science learner | 2023-02-06 |
Data science roadmap | MrMimic, Swami Chandrasekaran | Jobs linked to data science are becoming more and more popular. A bunch of tutorials could easily complete this roadmap, helping whoever wants to start learning stuff about data science. For the moment, a lot is got on wikipedia (except for codes, always handmade). Any help's thus welcome! | roadmap for learning DS | 20230-02-06 |
Data-science-best-resources | Tirthajyoti Sarkar | Data Science Collected Resources. A trove of carefully curated resources and links (on the topics of software, platforms, language, techniques, etc.) related to data science, all in one place. | comprehensive materials on DS | 2023-02-06 |
Sources | Introduction | Audience | Date |
---|---|---|---|
Python Basics | This course introduces the basics of Python 3, including conditional execution and iteration as control structures, and strings and lists as data structures. | Python beginners | 2023-02-15 |
Python for Everybody Specialization | This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. | Vocational Training | 2023-02-15 |
Programming for Everybody (Getting Started with Python) | This course aims to teach everyone the basics of programming computers using Python. | For beginners | 2023-02-15 |
Topics | Sources | Introduction | Audience |
---|---|---|---|
Kaggle Datasets | Kaggle | A great playground for coding practice and competition with abundant datasets | Easy to follow |
UCI Machine Learning Repository | UCI | A famous cite with abundant datasets | Classic dataset repo for ML |
Google Datasets | You know who is google | Giant | |
Awesome Public Datasets | Github | This is a list of a topic-centric public data sources in high quality among various applications | data scientists or practitiones |
Data World | dataworld | An official place full of data | Official |
World Bank | World Bank | An official place full of data | Official |
Datahub | Datahub | Datahub is the fastest way for individuals, teams and organizations to publish, deploy and share their data. | Anyone DS |
Earthdata | Earthdata | Your Gateway to NASA Earth Observation Data | Anyone DS |
CERN Data Portal | CERN | The CERN Open Data portal is the access point to a growing range of data produced through the research performed at CERN. | Anyone DS |
Topics | Introduction | Audience | Date |
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parsifal | Parsifal is a tool to support researchers to perform systematic literature reviews. | for writing SLR | 2023-02-08 |
litstudy | litstudy is a Python package that allows analysis of scientific literature from the comfort of a Jupyter notebook. It enables selecting scientific publications and study their metadata using visualizations, network analysis, and natural language processing. | for writing SLR | 2023-02-08 |
ASReview | The ASReview Universe consists of many many things, but on the whole, it is a research project conducted at Utrecht University. It uses state-of-the-art active learning techniques to solve one of the most interesting challenges in screening large amounts of text: there’s not enough time to read everything! Part of the universe is ASReview LAB, free and open source software for screening large amounts of textual data in a smarter way 🤓. | for writing SLR | 2023-02-08 |
livingPRISMAflow | Living systematic reviews should be reported in as much detail as possible, ideally using a standardised flow diagram to show the fate of all evidence identified, screened and included. The PRISMA 2020 flow diagram is the latest update of the PRISMA flow diagram. This package allows users to produce bespoke flow diagrams modelled after PRISMA. Users can choose whether to include 'previous' and 'other' arms of the flow diagram, and multiple updates are included from the template CSV file as separate columns in each box of the diagram. | for writing SLR | 2023-02-08 |
litstudy | litstudy is a Python package that enables analysis of scientific literature from the comfort of a Jypyter notebook. The package allows one to select scientific publications and study their metadata using visualizations, network analysis, and natural language processing. | for writing SLR | 2023-02-08 |
targetedSummarization | TextReducer is a tool for summarization and information extraction powered by the SentenceTransformer library. Unlike many techniques for extractive summaries, TextReducer has the option for a "target" around which the summary will be focused. This target can be any text prompt, meaning that a user can specify the type of information that they would like to find or summarize, and ignore everything else. | for summarizing text | 2023-02-10 |
Write a journal article in 12 weeks | In this workbook, Writing Your Journal Article in Twelve Weeks: A Guide to Academic Publishing Success, it take you through all the steps to revising a classroom paper, conference paper, or thesis chapter into a peer-reviewed journal article that you send to a journal. | Inexperienced writer | |
Stanford - Writing in the Sciences | This course teaches scientists to become more effective writers, using practical examples and exercises. Topics include: principles of good writing, tricks for writing faster and with less anxiety, the format of a scientific manuscript, peer review, grant writing, ethical issues in scientific publication, and writing for general audiences. | Inexperienced writer | |
How to Write and Publish a Scientific Paper (Project-Centered Course) | In this project-based course, you will outline a complete scientific paper, choose an appropriate journal to which you'll submit the finished paper for publication, and prepare a checklist that will allow you to independently judge whether your paper is ready to submit. | Inexperienced writer | |
Writing in English at University | Acquiring good academic research and writing skills early on is essential for your success both at university and in your professional life. | Inexperienced writer | |
Johns Hopkins - Introduction to Systematic Review and Meta-Analysis | We will introduce methods to perform systematic reviews and meta-analysis of clinical trials. We will cover how to formulate an answerable research question, define inclusion and exclusion criteria, search for the evidence, extract data, assess the risk of bias in clinical trials, and perform a meta-analysis. | For writing LSR | |
Quantitative and Qualitative Research for Beginners | This course is designed as a basic introduction to the complex world of research methods and provides both theoretical and practical information for students to give them a foundation for carrying out research in a wide range of disciplines using quantitative, qualitative, and mixed methods. | For anyone want to know Q&Q research |
Topics | Sources | Introduction | Audience | Date |
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Machine Learning Zoomcamp | Alexey Grigorev | Machine Learning Zoomcamp is a course based on the book, it's online and free, you can join at any moment. | For ML begineers and practioners | 2023-02-15 |
Machine learing for everyone | Blog | Clear blog materials with enough simplicity on machine learning knowledge | Beginners | |
Machine Learning for Beginners - A Curriculum | Microsoft | A 12-week, 26-lesson curriculum all about Machine Learning offered by Microsoft Azure. In this curriculum, you will learn about what is sometimes called classic machine learning, using primarily Scikit-learn as a library | Beginners | |
Awesome Machine Learning | josephmisiti | A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php. Moreover with resources: a list of free machine learning books, professional machine learning events, free machine learning courses available online, blogs and newsletters on data science and machine learning, free-to-attend meetups and local events | Anyone who is interested in AI knowledge | |
Deep Learning Drizzle | kmario23 | You can find nearly any learning resource about deep learning and machine learning etc, the only thing you have to consider is which is the best for you and how long you can finish it. A COMPREHENSIVE repo with deep learning, machine learning, reinforcement learning, optimizaition in machine learning, CV, NLP, Boot Camps or Summer Schools. | Anyone want to be a DL/ML professional | |
500 AI Coding Projects with Code | ashishpatel26 | 500 AI Machine learning Deep learning Computer vision NLP Projects with code !!! | Anyone who want to know AI by coding | |
Applied ML | eugeneyan | Curated papers, articles, and blogs on data science & machine learning in production. | ML stuff | 2023-02-13 |
Topics | Sources | Introduction | Audience | Date |
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Python for Data Analysis, 3E | O'reilly | The book has been updated for pandas 1.4.0 and Python 3.10. The changes between the 2nd and 3rd editions are focused on bringing the content up-to-date with changes in pandas since 2017. | Python learners | 2023-02-15 |
Automate the Boring Stuff with Python | Al Sweigart | In Automate the Boring Stuff with Python, you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand - no prior programming experience required. | Practical Programming for Total Beginners | 2023-02-13 |
Python Pandas Cheat Sheet | Google Drive | Here is a quick Python Pandas cheatsheet that covers some of the most common functions and operations you will use when working with Pandas | Beginners | |
The Filed Guide to Data Science | Google Drive | Comprehensive content, you can get big idea of data science from P74~75 | DS Practioners | |
MACHINE LEARNING LECTURE NOTES by MALLA REDDY COLLEGE | Google Drive | (R17A0534) Machine Learning, Objectives: Acquire theoretical Knowledge on setting hypothesis for pattern recognition. Apply suitable machine learning techniques for data handling and to gain knowledge from it. Evaluate the performance of algorithms and to provide solution for various real world applications. | ML Beginners | |
50 DAYS OF PYTHON | Google Drive | This book presents you with an opportunity to master some of the most important concepts and fundamentals of the Python language by solving challenges. There are more than 80 challenges in this book, and you are required to solve them in 50 days. Solve one challenge or two a day and go on about your business and by the end of 50 days, you will have mastered Python fundamentals. | Python player | |
Python Cheat Sheat | by Frank Andrade | Involving pandas, numpy, sklearn, matplotlib, seaborn, BS4, Selenium, Scrapy | Python Practioners | |
97 things every data engineer should know | by Tobias Macey of O'Reilly, | Collective Wisdom from the Experts, this book is a collection of advice from a wide range of individuals who have learned valuable lessons about working with data the hard way. To save you the work of making their same mistakes, we have collected their advice to give you a set of building blocks that can be used to lay your own foundation for a successful career in data engineering. | for data engineer |
Topics | Sources | Introduction | Audience |
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Data Analyst Roadmap | Github | Data Analytics is the process of exploring and analyzing large datasets to find hidden patterns, unseen trends, discover correlations, and derive valuable insights to make business predictions. It helps in Improved Decision Making, Better Customer Service, Efficient Operations, Effective Marketing and Improves the Speed and Efficiency of the business. | For DS beginners |
Topics | Sources | Introduction | Audience |
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Comic for Federate Learning | Blog | Interesting comic to understand federate learning, which is created by the federated learning team at Google AI. | Beginners |
Topics | Sources | Introduction | Audience |
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IoT for beginners | Github | Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about IoT basics. | Beginners |
Topics | Sources | Introduction | Audience |
---|---|---|---|
Heroes of Deep Learning: Geoffrey Hinton | Blog | Andrew sits down with Hinton to discuss his first exposure to AI, his current research projects, and his changing understanding of AI throughout the decades. | Anyone who is interested in AI knowledge |
Topics | Sources | Introduction | Audience |
---|---|---|---|
Data Science Interviews | Github | Data science interview questions - with answers, theoretical questions involving linear models, trees, neural networks and others, technical questions involving SQL, Python, coding etc. | Application for DS job |
- Collection of advice for prospective and current PhD students
- Awesome-PhD with tools and resources when starting PhD
- Grad School Advice by Jason Hong
- Advice for Research Students by Jason Eisner
- Advice for researchers and students by Michael Ernst
- Advice Collection by Tao Xie and Yuan Xie
- Awesome CS PhD application advice by Jed Yang
- CS PhD the greatest hits by Angela Jiang
- List of PhD reflections by Stephen Tu
- Useful computer vision PhD resources by Yana Hasson
- Checklists for Stat-ML PhD students by Aaditya Ramdas
- Grad School Resources by Kalpesh Krishna
- Tips and tricks to an awesome CS master thesis
- PhD Modelling Search and Stopping in IIR
- Awesome CS-Ja PhD Life
- PhD Tools
- How to write a good PhD thesis and survive the viva
- Nasty PhD Viva Questions (Extract)
- PhD Journey
- Writing a PhD Thesis
- Writing your paper: Everything you need to know to prepare and write an effective research paper
- Article submission and peer review: Your complete guide to submitting your research paper and navigating the peer review process
- Research impact: A guide to creating, capturing, and evaluating the impact of your research
- Choosing the right journal for your research: A comprehensive guide for researchers
- Advice on Applying to Grad School in Computer Science, here we can get concrete advices in computer science.
Whether you are writing a thesis, dissertation, or research paper it is a key task to survey prior literature and research findings. More likely than not, you will be looking for trusted resources, most likely peer-reviewed research articles. Academic research databases make it easy to locate the literature you are looking for. We have compiled the top list of trusted academic resources to help you get started with your research:
No | Database | Description |
---|---|---|
1 | Scopus | Scopus is one of the two big commercial, bibliographic databases that cover scholarly literature from almost any discipline. Beside searching for research articles, Scopus also provides academic journal rankings, author profiles, and an h-index calculator. |
2 | Web of Science | Web of Science also known as Web of Knowledge is the second big bibliographic database. Usually, academic institutions provide either access to Web of Science or Scopus on their campus network for free. |
3 | PubMed | PubMed is the number one resource for anyone looking for literature in medicine or biological sciences. PubMed stores abstracts and bibliographic details of more than 30 million papers and provides full text links to the publisher sites or links to the free PDF on PubMed Central (PMC). |
4 | ERIC | For education sciences, ERIC is the number one destination. ERIC stands for Education Resources Information Center, and is a database that specifically hosts education-related literature. |
5 | IEEE Xplore | IEEE Xplore is the leading academic database in the field of engineering and computer science. It's not only journal articles, but also conference papers, standards and books that can be search for. |
6 | ScienceDirect | ScienceDirect is the gateway to the millions of academic articles published by Elsevier. 2,500 journals and more than 40,000 e-books can be searched via a single interface. |
7 | Directory of Open Access Journals (DOAJ) | The DOAJ is very special academic database since all the articles indexed are open access and can be accessed freely of charge. |
Bibliography maker tools are some of the more helpful solutions for students and researchers alike. It’s no secret that many researchers wish to do away with this part after a laboring through their research methodology and other crucial parts of their papers. But various editing styles and their accompanying citation formats ensure that rendering this part of the paper does not come straightforward as it should.
Today, there is a plethora of solutions in the market that were not available decades ago. These include self-created databases and web-based citation generators (Emanuel, 2013). With an array of options available, one might be asking what’s the best citation generator to use.
No | Name | Description |
---|---|---|
1 | Mendeley Cite | Mendeley Cite is a plug-in for Microsoft Word that lets you cite sources without leaving your document. The plug-in appears in the References tab in Word which allows you to automatically add in-text citations and generate bibliographies. |
2 | Zotero | Zotero is a free, open-source research tool that lets you collect research material, organize them, and create references and bibliographies. Zotero has a downloadable desktop app for Mac and Windows. They also have Zotero Connector, a browser extension that allows you to save webpages online and sync it to the desktop app. |
3 | EndNote | Endnote is a complete reference management software that promises users to research smarter. Aside from your own library where you can gather, sort, and share your research, it also has a Cite-As-You-Write plug-in for Word and Mac. The plug-in bridges your EndNote library and Microsoft Word or Apple Pages so you can seamlessly cite sources without switching to different interfaces. |
4 | Paperpile | Paperpile is a subscription-based reference management system that lets you store, organize, and share your research all from one place. The paid version includes beta version of Word plug-ins for Mac and Windows. However, Paperpile also offers a free reference manager for Google Docs. |
5 | Cite This For Me | Cite This For Me has a decent amount of tools that will make citation easier and faster. Though it can only support a moderate number of source types, it makes up for it in the array of citation styles available. While it has the usual download, export, and copy-and-paste tools that other citation generators have, its collaboration features make it unique. |
6 | Citation Machine | Citation Machine is a free online bibliography generator that’s also straightforward to use. Like most citation generators, users are asked to identify the source material, look for it via URL or search term, and supply any missing information to complete the citation. |
7 | EasyBib | EasyBib is another free, easy-to-use online bibliography maker. Like Citation Machine, EasyBib is part of the online learning platform Chegg Service. This probably explains why it has a similar interface and features to Citation Machine. |
8 | BibMe | BibMe is an online bibliography generator that makes the tedious task of citation more convenient. |
9 | CiteMaker | Touting itself as a best-in-class referencing tool, CiteMaker is a bibliography maker that promises fast output in three easy steps (CiteMaker, n.d.). |
10 | Citefast | Citefast is an online citation generator that promises not only a free tool but also a fast one. Citefast can automatically generate citations out of web page URLs, ISBNs, and more. You can also type in the information yourself. Fields for reference data have tips that you can hover over so you know how to properly format your sources. |
11 | KnightCite | KnightCite is a free online citation generation service run by the Hekman Library at Calvin College. It was created by a student of the school with the aim of building a quick and reliable citation tool for other students (Calvin University, n.d.). |
12 | Citation Builder | Citation Builder is a free online bibliography maker hosted by the North Carolina State University library. It has a rather simplistic interface with dropdowns for the resource type and citation style. You just have to choose the options from the dropdown and manually fill out the needed information for the resource type. Once you hit Submit, it will generate a citation for you which you can then copy and paste to a document (NC State University, n.d.). |
13 | OttoBib | OttoBib is a straightforward online citation generator that lets you cite books using their International Standard Book Number (ISBNs). You can cite multiple ISBNs as long as they are separated with commas. OttoBib supports MLA, APA, Chicago/Turabian, BibTeX, and Wikipedia (OttoBib, n.d.). |
- International Journal on Informatics Visualization
- International Journal of Computing and Digital Systems
- International Journal of Sensor Networks | WoS indexed, Q4, around 6 months to 10 months.
- International Journal of Information and Computer Security | The longest time can be nearly 2 years!
- International Journal of Electronic Security and Digital Forensics | WoS indexed,Q4, around 1 year.
- International Journal of Communication Networks and Distributed Systems | WoS indexed, Q4, around 1 year to 1.5 year.
- International Journal of Security and Networks | around 1 year to 1.5 year.
- International Journal of Mobile Network Design and Innovation | around 1 year to 1.5 year.
- CMC-Computers, Materials & Continua | APC: $1,350 | ~ 4 months |
- IEEE Internet of Things Journal
- IEEE Transactions on Information Forensics and Security
- Information Sciences
- Future Generation Computer Systems
- Computers & Security
- Computers & Electrical Engineering
- Sensors
- Journal of Ambient Intelligence and Humanized Computing
- Alexandria Engineering Journal
- IEEE ACCESS
- Multimedia Tools and Applications
- Electronics
- Journal of Big Data
- Cybersecurity
- Arabian Journal for Science and Engineering
- Transactions on Emerging Telecommunications Technologies
- Mobile Information Systems
- Malaysian Journal of Computer Science (ISSN 0127-9084)
- KSII Transactions on Internet and Information
- Applied Science
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