Since the 17th century, and probably even earlier, taking notes has been a standard element of the learning process. Students taking notes with pens and paper in lecture halls or libraries has remained the same for ages.
The alternatives for studies are much broader now. You can take paper notes, but you can also type them on a laptop, videotape yourself explaining things on the phone, or enter your most important information into a flashcard study app for future reference.
This blog will discuss the importance of written notes/online notes and tips for taking online study notes related to Machine Learning(ML).
It would be best if you prepared for the lecture to take efficient notes. Consider what you want to learn, the topic of the lecture or other reading material, and how it relates to your work.
To learn more about the lecture’s topic and learning objectives as you prepare, you might start by reading the module guide. Read suggested books to become comfortable with new concepts, vocabulary, or language. Your professor may have suggested a little pre-reading, and Wikipedia is a good resource for general information on new subjects. Determine the essential elements you need to take down by considering how the lecture material connects to your tasks.
Be prepared to pay attention during a presentation. The speaker will introduce and then summarize the important themes at the beginning and end of the presentation, so pay close attention to these parts.
Don’t attempt to record every word that is stated. You can discover significant ideas by listening to words and phrases like “there are three basic reasons for…” or “on the other hand…” Watch for any references to additional sources you might want to check out.
Lecture capture technology is used to record the majority of lectures. You can complete any gaps in your lecture notes by watching the lecture once more.
On a tablet or laptop, Microsoft OneNote is excellent for making annotations on course materials. Using a pen, you can even turn handwritten notes into digital text. The student benefit Office 365 box includes a free download of OneNote.
Summarize your LectureNotes
Modules, weeks, or other time frames are used to divide up courses. You will be asked to internalize the materials from each period. It is highly possible that the course will provide notes or lecture slides that summarise the topic.
Make up your summary of the information for the session. You will need to make notes from the information you take in during the break and organize those notes into a logical structure before summarizing them.
Although it is frequently different, this may be the same structure that was used to display the material to you. It might be different because you’ll have connected the information to prior knowledge and be able to express it to yourself more clearly than it was originally provided.
For each module or week of material, aim for a summary of roughly one page. The amount of content will determine how this is done, but the goal is to distill the information into its essential ideas and lay out the connections between them. You may find all the information you require on those ideas in the source materials, such as the lecture video or required reading.
- After finishing the notes from a lecture or paper, I condense them into 5–20 flashcards. I hardly ever refer back to the initial notes after that.
- Every one to three days throughout the following days, I spend around 10 minutes reviewing the cards. Once it becomes regular, it doesn’t require much mental effort; I do it whenever I have a brief break.
- You can quickly tackle subject-specific material using books as a reference source. This use case does not fit the strategies in this section. The strategy in this section is for processing a book in a linear method from beginning to end, just like the strategies for processing a course were previously.
- Active reading is necessary to get the most out of the book and only have to touch it once.
- You’ll inevitably locate and study numerous publications on machine learning. Conference papers, journal articles, theses, and technical reports fall under this category. Gather these resources, their information, and links to them so you can quickly refer to them again.
When we need to refer back to our notes, many of us find it difficult to write relevant notes. To take and write great notes, you must adapt tactics that are beneficial for you. In the end, it seems that the most crucial thing is to take lecture notes in your own words, and to take the time to actually connect with and analyze your grasp of the concepts while you’re writing them down, as opposed to merely jotting down everything you hear verbatim. We suggest using the LectureNotes app, which IS designed to make note-making easy. LectureNotes will help you develop a deeper understanding of Machine Learning and aid you in cracking the course efficiently.