Hello Aspirant,

To get top colleges in CSE, AI&ML you need to get a very good rank. With this rank in COMEDK you can get admission in the below mentioned colleges-

• SAMBHRAM....cutoff 27105(CSE)
• MS ENGINEERING....cutoff 27234(CSE)
• CAMBRIDGE....cutoff 28283(AI&ML)
• VIVEKANANDA......cutoff 30053(CSE)
• Basaveshwar.....cutoff 30054(CSE)
• BANGALORE COLLEGE OF ENGINEERING.....cutoff 30175(CSE)
• SAHYADRI.....cutoff 31900( CSE Data science)
• ATME....cutoff 37006(CSE)
• GOPALAN....cutoff 38514(CSE)
• JAIN RESEARCH....cutoff 38899(CSE)
• GM INSTITUTE.....cutoff 39257(CSE)
• PES SHIVAMOGGA.....cutoff 40383(CSE)
• DON BOSCO....cutoff for CSE 42102 and for AI&ML cutoff 43276

You have chances to get medium colleges. You can expect average placement from this colleges. To grab good opportunities you have to prepare yourself more for off campus placements.

Cutoff keeps changing year to year. Keep in mind that your chances to grab a seat will vary on the following basis:

• number of seats available
• number of students applied for the same branch
• performance of the students
• the category you belong to etc.

Also, you can use this predictor to predict colleges based on your score:

COMEDK UGET College Predictor 2022 - Predict colleges based on your COMEDK Rank (careers360.com)

Check out previous year cutoff from the below link:

https://engineering.careers360.com/articles/comedk-uget-cutoff

Hope this information will help you .

Best wishes.

Hello student

I would suggest you to go with Artificial intelligence rather than machine learning.

AI has a very specific purpose of building an intelligent agent that can take rational decisions under various different circumstances. By its very nature, the intelligent agent needs to interact with environment that were built for humans and hence must be capable of human-like capabilities i.e reading natural language text, understanding speech, recognizing different objects etc. The application focus is something like, a robot capable of automatically identifying and fixing issues that can occur in a nuclear reactor or a robot capable of self navigation, experimentation and reporting "interesting" observations during extra planetary missions etc. From these application, we also get some higher order AI problems. For example, a robot self-navigating a planet, needs to plan and chart its course from point A to point B or a robot that is attempting to fix a leak in a nuclear reactor needs to identify the set of task to perform so that the leak is fixed.

The goal of ML is to assimilate known knowledge in an abstract form called models, and be able to predict certain unknowns for instances that will be seen in the future. For example, in an email spam classification task, the goal is to learn a model from a known set of emails that have been labeled as spam or not spam and be able to predict whether the new email that we just received is spam or not spam. Classification is just one concrete instantiation of ML goal. Clustering can be thought of as predicting cluster variables for future instances and Regression can be thought of as predicting function values for points that haven't been observed so far etc.

AI with its very specific application focus can use tools built in ML to achieve its goals. However, ML serves a much broader class of problems.

With these in mind, what you want to start from is entirely upto you. For example, if you want to build planet-navigating robots then you probably need to start from AI, learn about the various interesting problems involved in AI, see what kind of ML tools you will need to learn, come to ML learn those tools and go back to AI. However, if your interest lies in building the ML tools that serve a fairly broad class of problems many of which are relevant in the real world today [1], then you may want to start learning ML first.

Note that, both ML and AI are vast fields with many things to learn. Even though I suggest switching from ML to AI and AI to ML, it is not as easy as it might sound :-). Unless you know what you want to learn and how you plan to use it, you might be aimlessly going into and learning things, that may or may not be relevant to what you might want to do. Not that it is wrong, but, as humans, we have very limited time and we need to use it as efficiently as possible.


Machine learning is a scaled down version of A.I, crudely speaking.

Let me make it clear.

First the Objective part : There is a machine that needs to learn something, just like how a man can learn something. Now, just like how one can use different methods to learn : Some are very powerful methods to learn, some are less weaker methods; some methods require a lot of time and lot of effort, some are simple. Machines also have different methods to learn things.

A machine can learn based on simple and easy techniques like Machine learning. This is starting point for entry to A.I. But there can be much more complicated techniques like Abstraction, back-propagation etc. which help us identify and learn more difficult patterns.

At the heart of both is Pattern Recognition, which is the genesis of this entire field of A.I and M.L.

My suggestion is start with ML and then go for A.I.

Hello,

Power BI is a collection of software services, apps, and connectors that collaborate to link, convert, and clean data into a data model and produce charts for data visualisation. Of all BI tools, Power BI is regarded as the industry leader in business analytics. This has led to an ongoing increase in the need for certified Power BI personnel across the majority of leading MNCs. Therefore, people who are knowledgeable with Power BI ideas and have experience using it may make a good living and have the opportunity to work for prestigious companies. PayScale estimates that the average annual salary for a BI developer is 512,800 rupees ($74,400) in India and the United States, respectively.

Alright! Joining Power BI online training is the finest option, if you're asking me what the best resources are for learning Microsoft Power BI. As a result of this BI tool's popularity, several institutions began providing training in Power BI. In partnership with IBM, Intellipaat is one of the well-known training companies for Power BI.

Thank You

Hello Aspirant,

See If we go through the analysis of marks Vs Percentile Vs rank for JEE-Main 2021 then according to the percentile mentioned by you in the question your CRL rank is expected to be in the range of 560092 - 629625 .

Note that the rank which is predicted is only the expected rank on the basis of previous year's data so your actual rank might vary depending upon current factors.

On such rank you have some chances for AI & ML only in Sahyadri Valley College of Engineering and Technology, Pune.

To have a list of all those colleges which you can get based upon your JEE-Main score or rank you can use JEE-Main College Predictor:-

https://engineering.careers360.com/jee-main-college-predictor?icn=QnA&ici=qna_answer

On such percentile, being a SC candidate you have some chances to qualify for JEE-Advance 2022 but still the cutoffs for this year have not released yet officially.

As the cut-offs are released along with the JEE-Main 2022 result so for now you can get an idea from JEE-Main 2021 qualifying cut-offs that are enlisted below :-

==>> Common Rank List (CRL) - 87.8992241-100.0000000 Percentile

==>> GEN-EWS - 66.2214845-87.8950071 Percentile

==>> Other Backward Classes (OBC-NCL) - 68.0234447-87.8950071 Percentile

==>> Scheduled Caste (SC) - 46.8825338-87.8950071 Percentile

==>> Scheduled Tribe (ST) - 34.6728999 87.8474721 Percentile

==>> PwD - 0.0096375-87.8273359 Percentile

Note that in above table it is not the actual cut-off for JEE-Main 2022 but previous year's cut-off.

You can check out previous year's cut-off trends from the link given below :-

https://engineering.careers360.com/articles/jee-main-cutoff

I hope this information helps you.

Good Luck!!

IT IS A GOOD ONE FOR THE STOCK MARKET. Learning sharks gives amazing courses on grasping Financial Market. I'm doing Smart Investor courses which remember profundity information about Fundamentals information about shares, Technical Analysis, and Options Strategies.

The best financial exchange establishment is finding out about sharks, there is no discussion. Given how many tutors the learning sharks foundation has, learning sharks has 100+ long periods of involvement contrasted with ism's joined staff insight of 20 years.

Whether you are a fledgling or an expert, neither one of the establishments is better compared to the next. By and by, I'd like to read up about sharks for different reasons.

Hello
Deep Learning is known as a small branch of the Artificial Intelligence. With the help of a Deep Learning training, we can instruct our computers to learn for themselves in a way that gives us actionable outcomes.

Following are the Best Deep Learning Courses:

Best Overall Course: Deep Learning Nanodegree (Udacity)

Deep Learning Specialization (Coursera)

Complete Guide to TensorFlow for Deep Learning with Python (Udemy)

Deep Learning A-Z: Hands-On Artificial Neural Networks (Udemy)

An Introduction to Practical Deep Learning (Coursera)

Deep Learning, by 3Blue1Brown (YouTube)

Deep Learning: Recurrent Neural Networks in Python (Udemy)

Advanced AI: Deep Reinforcement Learning in Python (Udemy)

Deep Learning with Keras (Pluralsight)

Introduction to Deep Learning (Coursera)

The best Institutes for Deep Learning Courses in India are listed below:

Analytixlabs
Upgrad
Coursera
Udemy
Jigsaw Academy
Manipal ProLearn
Udacity
TalentSprint
Great Learning
ZekeLabs


The best way to learn about it is to go do it. Rob's suggestions of an intro course or a tutorial is a great way to get started, but really what you should do is try to solve some problem with NLP.

Here's how you might do that. Go download NLTK (Natural Language Toolkit). Then build some software that does something cool.

Here are some ideas:

Run a bunch of different POS taggers on some text and characterize the differences. Which is better for what domain? Do they make similar mistakes?
Build a sentiment analysis system and run it on a bunch of reviews, or tweets about something. See what mistakes it's making and figure out how to make it better. What features should you use that can help it do better? Find out if people liked the Interview, or whatever the movie du jour is!
Write a system to detect spam reviews on review sites. You can find a huge dataset here: Detect Fake Reviews and Reviewers or a smaller one here: http://myleott.com/op_spam/.
Build a system for some other language. Text segmentation in Chinese is fun and hard, but really pick any problem and apply it to another language, and you'll learn a huge amount about your assumptions about what works and what doesn't work.
None of these things will work well on your first try -- a key lesson in NLP, actually -- so the main thing you should focus on, once you get a baseline system working, is to figure out how to make your system better. That's 90+% of the effort in NLP.

Best of luck

hello student
The best colleges for artificial intelligence and machine which affiliated to Anna University are as follows:-

Note that these colleges are as per my view so it can vary from person to person.

Anna University Regional Campus, Coimbatore
College of Engineering, Guindy
Alagappa College of Technology, Chennai
MIT Chennai
UCEK Kancheepuram
University College of Engineering Bharathidasan Institute of Technology Campus Anna University, Tiruchirappalli
University College of Engineering, Ramanathapuram
University College of Engineering, Tindivanam
AAA College of Engineering and Technology, Thiruthangal
To get more information you can check out the link given below- https://www.careers360.com/university/anna-university-chennai/affiliated-colleges

hiiii

let me tell you one clear cut thing that if you want to get selected in a reputated government college then  you have to sacrifice your sleep and you have yo manage your valuable time like if you eat in 50 mints then you should try to eat the same food within 25-30 minutes then in rest of time either you can take a nap to energies your brain or you can revise your subjects.

if you are going to face your exam and you are not taking the coaching then you might face trouble during your entrence. but you have a option that you can drop a year for your entrance but 12th marks is important for participating in entrance minimum 60% should be in your marksheet for applying in entrance. I'll suggest you to focus in your school exam right now and then take a drop yaer and cllear your entrance.

best of luck aspirant.

Hello

The finest stock market institute is learning about sharks, there is no debate. Given the amount of mentors the learning sharks institute has, learning sharks has 100+ years of experience compared to ism's combined faculty experience of 20 years.

Whether you are a beginner or a professional, neither institute is better than the other. Personally, I'd prefer to study about sharks for a variety of reasons.

Thanks