How can I use ChatGPT for my term paper or bachelor thesis?
You can use ChatGPT to assist in the writing process for your research paper, thesis, or dissertation in the following ways:
You can use ChatGPT to assist in the writing process for your research paper, thesis, or dissertation in the following ways:
In classification, the goal is to assign input data to specific, predefined categories. The output in classification is typically a label or a class from a set of predefined options.
In regression, the goal is to establish a relationship between input variables and the output. The output in regression is a real-valued number that can vary within a range.
In both supervised learning approaches the goal is to find patterns or relationships in the input data so we can accurately predict the desired outcomes. The difference is that classification predicts categorical classes (like spam), while regression predicts continuous numerical values (like age, income, or temperature).
Algorithms are valuable to us because they:
Algorithms and computer programs are sometimes used interchangeably, but they refer to two distinct but interrelated concepts.
Algorithms and artificial intelligence (AI) are not the same, however they are closely related.
In computer science, an algorithm is a list of unambiguous instructions that specify successive steps to solve a problem or perform a task. Algorithms help computers execute tasks like playing games or sorting a list of numbers. In other words, computers use algorithms to understand what to do and give you the result you need.
A key challenge that arises in reinforcement learning (RL) is the trade-off between exploration and exploitation. This challenge is unique to RL and doesn’t arise in supervised or unsupervised learning.
Exploration is any action that lets the agent discover new features about the environment, while exploitation is capitalizing on knowledge already gained. If the agent continues to exploit only past experiences, it is likely to get stuck in a suboptimal policy. On the other hand, if it continues to explore without exploiting, it might never find a good policy.
An agent must find the right balance between the two so that it can discover the optimal policy that yields the maximum rewards.
Deep reinforcement learning is the combination of deep learning and reinforcement learning.
Some real-life applications of reinforcement learning include:
AI writing tools can be used to perform a variety of tasks.
Generative AI writing tools (like ChatGPT) generate text based on human inputs and can be used for interactive learning, to provide feedback, or to generate research questions or outlines.
These tools can also be used to paraphrase or summarise text or to identify grammar and punctuation mistakes. You can also use Scribbr’s free paraphrasing tool, summarising tool, and grammar checker, which are designed specifically for these purposes.
Unsupervised learning should be used when your data is unlabeled and your goal is to discover the inherent structure or pattern in the data.
This approach is helpful for tasks like clustering, association, and dimensionality reduction.
Supervised learning should be used when your dataset consists of labeled data and your goal is to predict or classify new, unseen data based on the patterns learned from the labeled examples.
Tasks like image classification, sentiment analysis, and predictive modeling are common in supervised learning.
Generative art is art that has been created (generated) by some sort of autonomous system rather than directly by a human artist. Nowadays, the term is commonly used to refer to images created by generative AI tools like Midjourney and DALL-E. These tools use neural networks to create art automatically based on a prompt from the user (e.g., “an elephant painted in the style of Goya”).
However, the term has been in use since before this technology existed, and it can also refer to any technique use by an artist (or writer, musician, etc.) to create art according to a process that proceeds autonomously – i.e., outside of the artist’s direct control. Examples of generative art that does not involve AI include serialism in music and the cut-up technique in literature.
A real-life application of machine learning is an email spam filter. To create such a filter, we would collect data consisting of various email messages and features (subject line, sender information, etc.) which we would label as spam or not spam. We would then train the model to recognize which features are associated with spam emails. In this way, the ML model would be able to classify any incoming emails as either unwanted or legitimate.
Traditional programming and machine learning are essentially different approaches to problem-solving.
In traditional programming, a programmer manually provides specific instructions to the computer based on their understanding and analysis of the problem. If the data or the problem changes, the programmer needs to manually update the code.
In contrast, in machine learning the process is automated: we feed data to a computer and it comes up with a solution (i.e. a model) without being explicitly instructed on how to do this. Because the ML model learns by itself, it can handle new data or new scenarios.
Overall, traditional programming is a more fixed approach where the programmer designs the solution explicitly, while ML is a more flexible and adaptive approach where the ML model learns from data to generate a solution.
Although the terms artificial intelligence and machine learning are often used interchangeably, they are distinct (but related) concepts:
In other words, machine learning is a specific approach or technique used to achieve the overarching goal of AI to build intelligent systems.
Our research into the best summary generators (aka summarisers or summarising tools) found that the best summariser available in 2023 is the one offered by QuillBot.
While many summarisers just pick out some sentences from the text, QuillBot generates original summaries that are creative, clear, accurate, and concise. It can summarise texts of up to 1,200 words for free, or up to 6,000 with a premium subscription.
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Our APA experts default to APA 7 for editing and formatting. For the Citation Editing Service you are able to choose between APA 6 and 7.
Yes, if your document is longer than 20,000 words, you will get a sample of approximately 2,000 words. This sample edit gives you a first impression of the editor’s editing style and a chance to ask questions and give feedback.
You will receive the sample edit within 24 hours after placing your order. You then have 24 hours to let us know if you’re happy with the sample or if there’s something you would like the editor to do differently.
Yes, you can upload your document in sections.
We try our best to ensure that the same editor checks all the different sections of your document. When you upload a new file, our system recognizes you as a returning customer, and we immediately contact the editor who helped you before.
However, we cannot guarantee that the same editor will be available. Your chances are higher if
Please note that the shorter your deadline is, the lower the chance that your previous editor is not available.
If your previous editor isn’t available, then we will inform you immediately and look for another qualified editor. Fear not! Every Scribbr editor follows the Scribbr Improvement Model and will deliver high-quality work.
Yes, our editors also work during the weekends and holidays.
Because we have many editors available, we can check your document 24 hours per day and 7 days per week, all year round.
If you choose a 72 hour deadline and upload your document on a Thursday evening, you’ll have your thesis back by Sunday evening!
Yes! Our editors are all native speakers, and they have lots of experience editing texts written by ESL students. They will make sure your grammar is perfect and point out any sentences that are difficult to understand. They’ll also notice your most common mistakes, and give you personal feedback to improve your writing in English.
Every Scribbr order comes with our award-winning Proofreading & Editing service, which combines two important stages of the revision process.
For a more comprehensive edit, you can add a Structure Check or Clarity Check to your order. With these building blocks, you can customize the kind of feedback you receive.
You might be familiar with a different set of editing terms. To help you understand what you can expect at Scribbr, we created this table:
| Types of editing | Available at Scribbr? |
|---|---|
| Proofreading Correction of superficial mistakes, such as typos, misspellings, punctuation errors and consistency errors. |
Yes! This is the “proofreading” in Scribbr’s standard service. It can only be selected in combination with editing. |
| Copy editing Focus on grammar, syntax, style, tone and the conventions of the field. The editor also considers the internal logic of the text and flags any obvious contradictions. |
Yes! This is the “editing” in Scribbr’s standard service. It can only be selected in combination with proofreading. |
| Line editing Focus on language, style, concision and choices. The editor helps you strengthen your story, polish your sentences and ensure that your use of language drives home your ideas. |
Yes! Select the Structure Check and Clarity Check to receive a comprehensive edit equivalent to a line edit. |
| Developmental editing (i.e. content editing, substantive editing) This is the first step of the editing process and applies to very early drafts. The editor helps you structure your ideas, decide what story to tell and find direction for your writing. |
No. This kind of editing involves heavy rewriting and restructuring. Our editors cannot help with this. |
When you place an order, you can specify your field of study and we’ll match you with an editor who has familiarity with this area.
However, our editors are language specialists, not academic experts in your field. Your editor’s job is not to comment on the content of your dissertation, but to improve your language and help you express your ideas as clearly and fluently as possible.
This means that your editor will understand your text well enough to give feedback on its clarity, logic and structure, but not on the accuracy or originality of its content.
Good academic writing should be understandable to a non-expert reader, and we believe that academic editing is a discipline in itself. The research, ideas and arguments are all yours – we’re here to make sure they shine!
After your document has been edited, you will receive an email with a link to download the document.
The editor has made changes to your document using ‘Track Changes’ in Word. This means that you only have to accept or ignore the changes that are made in the text one by one.
It is also possible to accept all changes at once. However, we strongly advise you not to do so for the following reasons:
You choose the turnaround time when ordering. We can return your dissertation within 24 hours, 3 days or 1 week. These timescales include weekends and holidays. As soon as you’ve paid, the deadline is set, and we guarantee to meet it! We’ll notify you by text and email when your editor has completed the job.
Very large orders might not be possible to complete in 24 hours. On average, our editors can complete around 13,000 words in a day while maintaining our high quality standards. If your order is longer than this and urgent, contact us to discuss possibilities.
Always leave yourself enough time to check through the document and accept the changes before your submission deadline.
Scribbr is specialised in editing study related documents. We check:
The fastest turnaround time is 24 hours.
You can upload your document at any time and choose between four deadlines:
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Yes, in the order process you can indicate your preference for American, British, or Australian English.
If you don’t choose one, your editor will follow the style of English you currently use. If your editor has any questions about this, we will contact you.