What is Machine Learning? | AI Concepts
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- Опубликовано: 7 фев 2025
- This video will help you to understand what is Machine Learning. Machine learning is a subfield of artificial intelligence. Machine Learning is defined as the capability of a machine to imitate intelligent human behavior. This video also explains the basics of building a Machine Learning Model.
#machinelearning
#ai
#datascience
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Course - artificial intelligence & mechine learning
Or
Artificial intelligence & datascience
Which combination is good
Choosing between AI & Machine Learning and AI & Data Science depends on your interests and career goals:
1. AI & Machine Learning: Focuses on algorithms and methods for machines to learn from data. Ideal for developing AI technologies and research in AI. Career paths include machine learning engineer and AI researcher.
2. AI & Data Science: Combines AI with data analysis and interpretation. Suitable for applying AI in business analytics and data-driven decision making. Career options include data scientist and AI analyst.
- Choose based on your interest in technical AI (Machine Learning) or AI's application in data analysis (Data Science).
- Consider your career aspirations and the industry you want to work in.
- Both fields are interrelated and valuable in the tech industry.
Well explained 👍👍👍
I am new subscriber.Enik artificial intelligentine kurich kooduthal padikkanam enghane start cheyyym?
@NinaMehanz Check out this video; it's a good one: ruclips.net/video/MhCHrvfAXlc/видео.htmlsi=FTKeFB2vGDxQytko by @codebasics
Sir BTec Artificial intelligence ,and data science ,aanoo BTec computer science and engineering (Artificial intelligence and robotic aataanu better
My Openion, it depends on the syllabus, college, and your interest.
what will the future job oppertunities in ml catagory?
Yes, AI and machine learning are getting bigger and bigger. They will keep growing for the next few years. Certainly! Here are the top 10 job opportunities in the field of machine learning (I got from internet):
1. Machine Learning Engineer: Developing, deploying, and maintaining machine learning models and systems.
2. Data Scientist: Analyzing data and extracting insights using machine learning techniques.
3. AI Research Scientist: Advancing AI and ML through research and innovation.
4. AI/ML Product Manager: Overseeing the development and launch of AI/ML-powered products.
5. Deep Learning Engineer: Specializing in creating and optimizing deep neural networks.
6. Natural Language Processing (NLP) Engineer: Working on language-related applications like chatbots and language translation.
7. Computer Vision Engineer: Developing systems for visual information interpretation.
8. AI Ethics and Bias Officer: Addressing ethical concerns and biases in AI systems.
9/ ML Operations (MLOps) Engineer: Managing the deployment and maintenance of ML models in production.
10. AI/ML Consultant: Helping businesses leverage AI/ML for specific problems or processes.
These roles are in high demand and offer exciting opportunities for those with expertise in machine learning and artificial intelligence.
Thankyou
Machine learning algorthm - ANN,Random forest and LSTM ithil ettavum nallath nth ann oru beginner padikann
@fathimakhan2777 I'm not an expert, but after checking online, I found that Random Forest is the easiest for beginners. Once you're comfortable with the basics, you can move on to ANNs, and then learn advanced models like LSTMs.
Thankyou❤️
You’re welcome 😊
Sir,a bio student can take ai and ml engineering. Is it tough
Hi, I am not sure about your knowledge in programming and math. In general, grasping complex math and gaining programming skills in Python can be tough initially. However, by dedicating time to mastering these technologies, you'll be able to leverage your biotech knowledge and integrate it with AI and ML applications. I would suggest trying a short-term course first. If that works, then continue your learning. It is hard to make a decision without exploring the subject.
@@LearnWithAji ok
Njan commerce stream ahn . Enikk artificial intelligence orupad interest olla oru person ahn njan enikk ith padikkan pattumo ?😊
yes for sure. 'youtube' il lots of videos undu about AI. Watch a few of them to understand the basics. If you feel comfortable, then enroll in an online short course. If that works well, you can join a longer course. Let me know if you need any additional info. Good luck
@@LearnWithAji thankyou so much for your response ❤️
machine learining ill DSA evidelum use ondo?
Yes, DSA (Data Structures and Algorithms) are like the ABCs of programming. It's essential to learn them, no matter what you're studying.
Sir can i take this course after completing Bcom Ca? I'm confused
That dependes on your interests. There are lots of basic videos in 'youtube'. Watch a few of them to understand the basics. If you feel comfortable, then enroll in an online short course. If that works well, you can join a longer course. Let me know if you need any additional info. Good luck!
Sir plus two kazhijit machine learning skills okke padicha joli kituoo??
You can send me your number if you want to talk: learnwaji@gmail.com
Sir ipol ee coursenu scope ondoo
Yes, AI and machine learning will continue to grow for many years. So there will be many opportunities in this field.
@@LearnWithAji is bca is god for this study
@@LearnWithAjinjn bcom ca kazhinjath aane enik ee course cheyan pattumo?
Sir, can a bba graduate can study this course, is it tough ❓
Certainly! My suggestion is, you might start by exploring free online courses or watching RUclips videos to grasp the basics of machine learning. This will help you determine if you’re interested and comfortable with the mathematical and programming aspects. Based on this initial learning, you can then decide whether to pursue more advanced studies. Good luck🤞
Njnum bcom kazhinjathe😅 ee course padikan pattumo oru samshayam und
Feel free to email me if you want to talk more: learnwaji@gmail.com
Sir ithu padikkan plus two kazhinje enthanu edukkendathe
Machine Learning oru Statistics based science aanu. Choose any course that has Coding, Maths & statistics. Engineering aanel Computer Science engg edukam. BSc aanel BSc Maths/ Statistics eduthit koode coding courses self learn/ certifications cheyyam. Data Science / Artificial Intelligence padipikkunna courses um ipo dharalam und. choose based on the syllabus.
Hope this helps.
@TheDataArtistry, thank you for your response. It's a great answer. Thanks again 😊 I see that you created some nice data science slides on Instagram.
@@LearnWithAji Thank you for the kind words. You too created informative videos.
👍🏻
After mechanical engineering eee course cheyamo?
Yes, of course. But my recommendation is to get familiar with the topic by watching a few beginner RUclips videos and then do a short-term specialization course. Then, you can make a decision.
Also please read other comments in this video.
Artificial intelligence mechn learning artificial intelligence Robot ettanu better
Ee topics ellaam relevant topics aanu and related topics aanu. Enthaanu better ennu chodichaal it depends. Machine learning aanu padichu thudangaan nallathu.
ഇതക്കെ പഠിപ്പിക്കുന്ന നല്ല സ്ഥാപനം പറഞു തരോ bro
AI പഠിക്കുന്നതിനുള്ള general ആയി മൂന്ന് രീതികൾ ആണ് എനിക്ക് തോന്നുന്നത്.
1.കോളേജ് ഡിഗ്രി: AI-യിൽ ബിരുദം, ബി.ടെക്, എം.ടെക് പോലുള്ള ഡിഗ്രി പ്രോഗ്രാമുകൾ പൂർത്തിയാക്കാം.
2. ഷോർട്ട് ടേം കോഴ്സുകൾ: AI-യിൽ സർട്ടിഫിക്കറ്റ്, ഡിപ്ലോമ കോഴ്സുകൾ പോലുള്ള short term കോഴ്സുകൾ നിങ്ങൾക്ക് തിരഞ്ഞെടുക്കാം.
3. ഓൺലൈൻ ലേണിംഗ്: AI-യിൽ നിരവധി ഓൺലൈൻ കോഴ്സുകളും ട്യൂട്ടോറിയലുകളും ലഭ്യമാണ്. Coursera, edX, Udemy പോലുള്ള പ്ലാറ്റ്ഫോമുകളിൽ നിങ്ങൾക്ക് ഈ കോഴ്സുകൾ കണ്ടെത്താം.
നിങ്ങളുടെ educational background, interests എന്നിവ അനുസരിച്ചാണ് തീരുമാനം എടുക്കേണ്ടത്. ഏതായാലും നല്ല പോലെ അന്വേഷിച്ച് മനസ്സിലാക്കുക, എന്നിട്ട് തീരുമാനം എടുക്കുക
എന്തെങ്കിലും ചോദ്യങ്ങളുണ്ടെങ്കിൽ, പോസ്റ് ചെയ്തു കൊള്ളൂ.
കോളേജുകളെക്കുറിച്ചും കോഴ്സുകളെക്കുറിച്ചു detailed ആയി പറയാനുള്ള knowledge എനിക്കില്ല. Sorry bro!
Contact number tharuo
The corrected sentence would be:
Sure, can you message me at form.jotform.com/learnat25/contact-me? I will send my contact number back to your email.