sample_output.csv

source,scraped_at,url,sku,title,question_url,question_id,answer_id,answer_count,author,author_url,author_credential,author_is_verified,text,text_chars,upvotes,views,shares,comments,created_at,updated_at,date_text,is_machine_answer,is_translated,language,category,mode,data_source,page,position
www.quora.com,2026-09-15T12:35:22.190442+00:00,https://www.quora.com/What-is-machine-learning-4/answer/Naushin-Ara-6,www.quora.com/What-is-machine-learning-4/answer/Naushin-Ara-6,What is machine learning?,https://www.quora.com/What-is-machine-learning-4,4256391,1477743913929252,253,Naushin Ara,https://www.quora.com/profile/Naushin-Ara-6,,False,"Machine Learning (ML) is a field of Artificial Intelligence that focuses on developing systems capable of learning from data, identifying patterns, and continuously improving their performance with minimal human intervention.",225,3,162,1,0,2026-07-25T07:13:30.376859Z,,Jul 25,False,False,en,What-is-machine-learning-4,question,dom+inline,1,1
www.quora.com,2026-09-15T12:35:22.190898+00:00,https://www.quora.com/What-is-machine-learning-4/answer/Anil-Yadav-7999,www.quora.com/What-is-machine-learning-4/answer/Anil-Yadav-7999,What is machine learning?,https://www.quora.com/What-is-machine-learning-4,4256391,1477743744691014,253,Anil Yadav,https://www.quora.com/profile/Anil-Yadav-7999,former Data Scientist at Multinational Corporations,False,"Hey, future ML engineers!!
Machine Learning is not a tough subject; it's all about regression models, data processing, clustering, and all these concepts.
- This is a very interesting subject that is like having a smart assistant who learns from examples.
Just like how you learn from practice and experience, ML algorithms learn patterns from data to make predictions or decisions without being explicitly programmed. Moreover, it's like teaching a computer to recognize cats in pictures by showing it lots of cat and non-cat images, so it can identify cats on its own in new pictures.
Note: Learning this subject, especially in today's world, is very beneficial career-wise, with many opportunities. There are many engineers, but ML engineers are in high demand, with salary prospects ranging from 5 to 12 LPA.
So why not start it as your full-time career?
But how can you learn it?
🟨 You can begin with reading books because books are true friends of learning where you can understand the basic concepts of regression models, clustering, support vector machines, and more.
🟪Next, YouTube is there with tutorials and videos of experienced engineers who have worked in this field; they will help you gain insight into an ML career. For true mentorship, courses will help especially in placement.
Some top ML courses highly rated by many people in Google searches include:
> - Pluralsight📓(Foundations of Statistics and Probability for Machine Learning Course with ML student libraries and assignments)
> - Learnbay📓(Advanced AI & ML Certification Program for Tech Professionals Course with capstone IBM projects and certification)
> - Alison📓(Machine Learning In Python Environment Course with modules and assessment of ML concepts for free)
In these resources, you can learn a lot about data cleaning, clustering testing, and many algorithms that are very important in ML. You will learn about data sets, tree models, PCA, etc.
So, after learning and acquiring skills in any one subject, you can fulfill your dream of a good job position, a good salary, and abroad networking opportunities, so why not understand and ace it?
I hope this answer helps you!",2156,125,1734,0,0,2024-03-07T08:31:46.062197Z,,2y,False,False,en,What-is-machine-learning-4,question,dom+inline,1,3
www.quora.com,2026-09-15T12:35:22.191046+00:00,https://www.quora.com/What-is-machine-learning-4/answer/Shahid-Shakeel-20,www.quora.com/What-is-machine-learning-4/answer/Shahid-Shakeel-20,What is machine learning?,https://www.quora.com/What-is-machine-learning-4,4256391,1477743746180099,253,Shahid Shakeel,https://www.quora.com/profile/Shahid-Shakeel-20,Data Scientist at Multinational Corporations (2019-present),False,"Machine Learning is a subset of Artificial Intelligence that prioritizes the development of algorithms and statistical models. Machine learning algorithms help computers learn from data. Also, the equipped data progresses the work of decision-making and identifying patterns. 📊🔎✍
Machine learning incorporates the imitation of human behaviors and works accordingly without the intervention of a human.
- Supervised Learning, Unsupervised Learning, Reinforcement Learning, etc. are some of the crucial parts of Machine Learning. 👈👈
Now, this subject is practical. That means you have to work practically to learn and implement in real-world situations.
If you are eager to learn Machine Learning, you can pursue courses available online.
> - Advanced Machine Learning Specialization from Coursera, Advanced AI and ML Certification Program from Learnbay (Domain Electives), Machine Learning Engineer Nanodegree from Udacity, etc. are some of the online courses to learn Machine Learning. ✅✅
Coursera’s course will teach you about reinforcement learning, natural language processing, Bayesian methods, etc. Also, Learnbay’s course covers advanced topics with various simulated real-time and capstone projects. Whereas, Udacity’s course teaches about supervised learning, unsupervised learning, reinforcement learning, etc. 📚📚
🤝Ending Statement:
This is a technical subject and you have to learn with projects only. As much as you practice with projects, your professional skills will be enhanced and you will get chances to expand your career further.
Thank You!",1559,109,894,6,0,2024-03-13T08:20:00.622356Z,2024-03-13T08:20:21.057174Z,2y,False,False,en,What-is-machine-learning-4,question,dom+inline,1,4
www.quora.com,2026-09-15T12:35:22.191225+00:00,https://www.quora.com/What-is-machine-learning-4/answer/Sheera-23,www.quora.com/What-is-machine-learning-4/answer/Sheera-23,What is machine learning?,https://www.quora.com/What-is-machine-learning-4,,,,Sheera,https://www.quora.com/profile/Sheera-23,Data Scientist JR. at Multinational Corporations,,"A branch of artificial intelligence (AI) and computer science called machine learning combines data and algorithms to simulate how people learn, gradually increasing its accuracy. Storage and processing advances over the past two decades have made it possible for some innovative machine learning-based systems, such as Netflix's recommendation engine and self-driving cars. Machine learning is a critical component of the rapidly expanding discipline of data science. Algorithms are taught using statistical approaches to produce classifications or predictions and to find critical insights in data m Continue Reading A branch of artificial intelligence (AI) and computer science called machine learning combines data and algorithms to simulate how people learn, gradually increasing its accuracy. Storage and processing advances over the past two decades have made it possible for some innovative machine learning-based systems, such as Netflix's recommendation engine and self-driving cars. Machine learning is a critical component of the rapidly expanding discipline of data science. Algorithms are taught using statistical approaches to produce classifications or predictions and to find critical insights in data mining operations. How machine learning works A Decision Process: Machine learning algorithms are typically used to create a prediction or classification. Your algorithm will generate an estimate about a pattern in the data based on some input data, which can be labeled or unlabeled. An Error Function: An error function evaluates the model's prediction. If there are known instances, an error function can compare to determine the model's accuracy. A Model Optimization Process: If the model can fit the data points in the training set better, weights are modified to narrow the gap between the known example and the model prediction. The algorithm will repeat this ""evaluate and optimize"" procedure, updating weights autonomously until an accuracy criterion is reached. What is the significance of machine learning? Machine learning is significant because it provides organizations with insights into trends in customer behavior and business operating patterns, as well as assisting in the development of new products. Machine learning is fundamental to the operations of many of today's biggest organizations, like Facebook, Google, and Uber. For many businesses, machine learning has become a crucial competitive differentiation. Learning the trade can only help you. Machine learning is a wonderful skill and has many career opportunities . There are many courses available today that can help you so much in building a career in machine learning. Developing expertise in those skills is the first step. One of the most famous machine learning courses is offered by Edureka. Let’s look at their features: It is a website where you may take technology courses in a variety of fields. For those who want to study more, there are certifications and course choices. Edureka provides courses in these fields that are approved by NIT Warangal (NITW) and E & ICT Academy. Edureka provides access to the course and assistance with it long after you have completed the training. The courses' principal disadvantage is that they do not give domain-specific instruction. There are various other courses as well. The only institute that has no notable disadvantages is Learnbay. They offer the best machine learning courses in Bangalore which can be accessed from anywhere. Course Name: Artificial Intelligence and Machine Learning Program Let’s look at what makes them the best. Domain specialization: Recruiters seek individuals with knowledge in a specific domain. You will be able to select from a number of specialties as part of your training, including BFSI, Telecom, Manufacturing, and Communication. Everything you need is available at Learnbay! Simulated Real-time and capstone projects: You will have the opportunity to work on real-time and capstone projects that will provide you with industry experience and will help you to improve your skills, knowledge, and resume. IBM Verified Certificate: Learnbay offers IBM and microsoft certifications that are internationally recognized, making it easier to find work. Some other additional features of Learnbay includes: Hybrid programs are accessible for students who want the flexibility of mixing online and classroom learning. In the project innovation laboratory, you can do tasks while being monitored by MAANG specialists at different Learnbay locations across the country. Delhi, Bangalore, Mumbai, and Pune are home to four of the seven destinations. Bottom line Machine learning is a wonderful career to get into. There are growing opportunities in machine learning everywhere and it is a good time to learn the skills. In my opinion, Learnbay is the best place to learn these skills. They have excellent placement assistance services as well. Best wishes!",4937,,,,,,,2y,,,en,What-is-machine-learning-4,question,dom,1,6
www.quora.com,2026-09-15T12:35:22.191445+00:00,https://www.quora.com/What-is-machine-learning-How-is-it-useful/answer/Michal-Krombholz,www.quora.com/What-is-machine-learning-How-is-it-useful/answer/Michal-Krombholz,What is machine learning?,https://www.quora.com/What-is-machine-learning-How-is-it-useful,,,,Michal Krombholz,https://www.quora.com/profile/Michal-Krombholz,Software Engeneer · Author has 217 answers and 96.7K answer views,,"Or better question is how is it different from normal computer programs? Computers are dumb. They can take a number from somewhere (a memory) or two and do some basic arithmetic on it and store result somewhere else. They can compare numbers and decide to start executing something else depending on result (an “if this then that” rule). That’s basically all they can do. It takes billions of such small steps to produce the result you see on this screen. It all has to be coded in similar fashion to a cooking recipes - painfully step by step. Computers are dumb but very fast at it, running billions Continue Reading Or better question is how is it different from normal computer programs? Computers are dumb. They can take a number from somewhere (a memory) or two and do some basic arithmetic on it and store result somewhere else. They can compare numbers and decide to start executing something else depending on result (an “if this then that” rule). That’s basically all they can do. It takes billions of such small steps to produce the result you see on this screen. It all has to be coded in similar fashion to a cooking recipes - painfully step by step. Computers are dumb but very fast at it, running billions of such small steps per second. Hence, to make anything happen the programmer has to know the ‘algorithm’ to write the recipe. You know the ‘algorithm’ that describes a line? Yes: y=a*x+b so you can draw a line by computing y (height on the screen) for every x (width of the screen) and lit a display pixel at such (x,y) coordinates. You get the idea. Now what if you did not know the algorithm? Say you have some observations about world, perhaps a list of search questions on google that you want to relate to a weather patterns of when they were asked? We do not know the algorithm for this hence we cannot code a program that given a serach query would predict the weather it may be related to. Enter “machine learning”. Imagine you have a magic box: it has input, output and two buttons on top: “good”, “bad”. For each input of <search question> the <weather pattern> appears on output. You then run your data set and for each entry applied to the input you get an output. You decide if the produced output is “good” or “bad” by pressing a button when you compare it with your data. After you have run through the data set, and prompted the box with good or bad buttons, the box “somehow learned” the correct response and now can produce good outputs for any input even for input it never saw before. It will “guess” (predict), in more “educated” manner. The box is a computer with a special, but very generic program that can learn and remember the correlation between input and output given a help from you (or rather the dataset). The key is that it’s a mathematical operation of “correlating” of input (words converted to numbers) to output (in numbers again but for human convenience here converted back to words). That is in short “machine learning”. The result of learning is remembered as a big set of numbers (a matrix) in memory but there is no true “computer algorithm” that was created in the process, as it was the case of “programming the algorithm” above. You can see how it’s very useful in cases where an algorithm is not known.",3271,,,,,,,1y,,,en,What-is-machine-learning-4,question,dom,1,16