Infosys hiring Data Scientist
Apply link: https://career.infosys.com/jobdesc?jobReferenceCode=INFSYS-EXTERNAL-209078&sourceId=4003
Apply link: https://career.infosys.com/jobdesc?jobReferenceCode=INFSYS-EXTERNAL-209078&sourceId=4003
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
๐ ๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ผ๐บ๐ฝ๐๐๐ฒ๐ฟ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐ณ๐ฟ๐ผ๐บ ๐๐ฎ๐ฟ๐๐ฎ๐ฟ๐ฑ, ๐ฆ๐๐ฎ๐ป๐ณ๐ผ๐ฟ๐ฑ, ๐ ๐๐ง & ๐๐ผ๐ผ๐ด๐น๐ฒ๐
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Basics of Machine Learning ๐๐
Machine learning is a branch of artificial intelligence where computers learn from data to make decisions without explicit programming. There are three main types:
1. Supervised Learning: The algorithm is trained on a labeled dataset, learning to map input to output. For example, it can predict housing prices based on features like size and location.
2. Unsupervised Learning: The algorithm explores data patterns without explicit labels. Clustering is a common task, grouping similar data points. An example is customer segmentation for targeted marketing.
3. Reinforcement Learning: The algorithm learns by interacting with an environment. It receives feedback in the form of rewards or penalties, improving its actions over time. Gaming AI and robotic control are applications.
Key concepts include:
- Features and Labels: Features are input variables, and labels are the desired output. The model learns to map features to labels during training.
- Training and Testing: The model is trained on a subset of data and then tested on unseen data to evaluate its performance.
- Overfitting and Underfitting: Overfitting occurs when a model is too complex and fits the training data too closely, performing poorly on new data. Underfitting happens when the model is too simple and fails to capture the underlying patterns.
- Algorithms: Different algorithms suit various tasks. Common ones include linear regression for predicting numerical values, and decision trees for classification tasks.
In summary, machine learning involves training models on data to make predictions or decisions. Supervised learning uses labeled data, unsupervised learning finds patterns in unlabeled data, and reinforcement learning learns through interaction with an environment. Key considerations include features, labels, overfitting, underfitting, and choosing the right algorithm for the task.
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ENJOY LEARNING ๐๐
Machine learning is a branch of artificial intelligence where computers learn from data to make decisions without explicit programming. There are three main types:
1. Supervised Learning: The algorithm is trained on a labeled dataset, learning to map input to output. For example, it can predict housing prices based on features like size and location.
2. Unsupervised Learning: The algorithm explores data patterns without explicit labels. Clustering is a common task, grouping similar data points. An example is customer segmentation for targeted marketing.
3. Reinforcement Learning: The algorithm learns by interacting with an environment. It receives feedback in the form of rewards or penalties, improving its actions over time. Gaming AI and robotic control are applications.
Key concepts include:
- Features and Labels: Features are input variables, and labels are the desired output. The model learns to map features to labels during training.
- Training and Testing: The model is trained on a subset of data and then tested on unseen data to evaluate its performance.
- Overfitting and Underfitting: Overfitting occurs when a model is too complex and fits the training data too closely, performing poorly on new data. Underfitting happens when the model is too simple and fails to capture the underlying patterns.
- Algorithms: Different algorithms suit various tasks. Common ones include linear regression for predicting numerical values, and decision trees for classification tasks.
In summary, machine learning involves training models on data to make predictions or decisions. Supervised learning uses labeled data, unsupervised learning finds patterns in unlabeled data, and reinforcement learning learns through interaction with an environment. Key considerations include features, labels, overfitting, underfitting, and choosing the right algorithm for the task.
Free Resources to learn Machine Learning: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
ENJOY LEARNING ๐๐
โค4
Forwarded from Web Development
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Forwarded from Data Analyst Jobs
Zelestra is hiring Junior Data Scientist ๐
Qualification : Bachelor's degree
Experience : 0-2 Years
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Qualification : Bachelor's degree
Experience : 0-2 Years
Location :; Gurugram
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All the best ๐
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
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Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
๐ ๐ฎ๐๐๐ฒ๐ฟ ๐ฃ๐ฟ๐ผ๐บ๐ฝ๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ!๐
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๐ช๐ฒโ๐ฟ๐ฒ ๐๐ถ๐ฟ๐ถ๐ป๐ด: ๐๐/๐ ๐ ๐๐ป๐๐ต๐๐๐ถ๐ฎ๐๐๐! ๐
Are you passionate about Gen-AI, LLMs, and cutting-edge ML tech?
๐ช๐ฒ'๐ฟ๐ฒ ๐ผ๐ป ๐๐ต๐ฒ ๐น๐ผ๐ผ๐ธ๐ผ๐๐ ๐ณ๐ผ๐ฟ ๐ฎ ๐ฐ๐๐ฟ๐ถ๐ผ๐๐ ๐บ๐ถ๐ป๐ฑ ๐๐ถ๐๐ต ๐ฌโ๐ญ ๐๐ฒ๐ฎ๐ฟ๐ ๐ผ๐ณ ๐ฒ๐ ๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ถ๐ป ๐๐/๐ ๐ (๐ฃ๐๐๐ต๐ผ๐ป-๐ณ๐ผ๐ฐ๐๐๐ฒ๐ฑ) ๐๐ผ ๐ท๐ผ๐ถ๐ป ๐ผ๐๐ฟ ๐ด๐ฟ๐ผ๐๐ถ๐ป๐ด ๐๐ฒ๐ฎ๐บ ๐ถ๐ป ๐๐ต๐บ๐ฒ๐ฑ๐ฎ๐ฏ๐ฎ๐ฑ (๐ช๐ผ๐ฟ๐ธ ๐ณ๐ฟ๐ผ๐บ ๐ข๐ณ๐ณ๐ถ๐ฐ๐ฒ).
๐ What weโre looking for:
โจ Experience with Hugging Face, GPT-3.5/4, Claude, or similar tools
๐ Familiarity with NLP tasks (summarization, NER, sentiment analysis)
๐ง Bonus: Knowledge of RAG, vector DBs, prompt engineering & LLM orchestration
If you're constantly exploring GitHub, reading research papers, and love building with AIโwe want to hear from you!
๐ง Share your resume at hr@nextgensoft.io
Are you passionate about Gen-AI, LLMs, and cutting-edge ML tech?
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๐ What weโre looking for:
โจ Experience with Hugging Face, GPT-3.5/4, Claude, or similar tools
๐ Familiarity with NLP tasks (summarization, NER, sentiment analysis)
๐ง Bonus: Knowledge of RAG, vector DBs, prompt engineering & LLM orchestration
If you're constantly exploring GitHub, reading research papers, and love building with AIโwe want to hear from you!
๐ง Share your resume at hr@nextgensoft.io
โค3
Forwarded from AI Prompts | ChatGPT | Google Gemini | Claude
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Forwarded from Data Analyst Jobs
EY is hiring!
Position: Data and Analytics
Qualifications: Bachelor's degree
Salary: 6 - 13 LPA (Expected)
Experience: Experienced
Location: Bangalore, India
๐Apply Now: https://careers.ey.com/ey/job/Bengaluru-Data-and-Analytics-Pricing-and-Commercial-Senior-KA-560016/1200004101/
๐WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
๐Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
All the best ๐๐
Position: Data and Analytics
Qualifications: Bachelor's degree
Salary: 6 - 13 LPA (Expected)
Experience: Experienced
Location: Bangalore, India
๐Apply Now: https://careers.ey.com/ey/job/Bengaluru-Data-and-Analytics-Pricing-and-Commercial-Senior-KA-560016/1200004101/
๐WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J
๐Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
All the best ๐๐
โค3
Societe Generale is hiring!
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Experience: Freshers/ Experienced
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Position: Business Analyst
Qualifications: Bachelorโs/ Master's Degree
Salary: 6.5 - 12 LPA (Expected)
Experience: Freshers/ Experienced
Location: Bangalore, India (Hybrid)
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All the best! ๐๐
Forwarded from Web Development
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โ React, Node.js, Express.js
โ MongoDB, REST APIs
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Forwarded from Python for Data Analysts
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