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8 292
𝗧𝗼𝗽 𝟱 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
1)Data Science Foundations
2)SQL for Data Science
3)Python for Data Science
4)Introduction to Data Science
5)Data Science Projects
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8 292
Infeneon Hiring !!
Role - Data Scientist
Exp - 1 year
Location- Bangalore
https://jobs.infineon.com/careers/job/563808957790879?domain=infineon.com#!source=400
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Looking for a Data Scientist Intern
Location: Bangalore (Whitefield)
Duration: 6 months
Ready to kickstart your career in data science? share your CV careers@neewee.ai
Don't miss this opportunity to grow your skills and make an impact. Tag your friends or connections who might be interested!
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𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗖𝗶𝘁𝗶 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 😍
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Remote Data Systems Analyst
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👉WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
👉Telegram Channel: https://t.me/dataanalyticsbuddy
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Wishing you lots of success in your career👍👍
8 292
Divya Staffing Solution Data Scientist
Exp: Fresher
https://www.linkedin.com/jobs/view/4132682181
8 292
𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 😍
1) Generative AI
2) Big data artificial intelligence
3 ) Microsoft Al for beginners
4) Prompt Engineering for Chat GPT
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8 292
Repost from AI Jobs | Artificial Intelligence
Google's Applied ML team is hiring:
Hiring for skilled ML engineers in Bangalore to work on edge optimization and acceleration of GenAI and non-GenAI models for google's Edge TPU.
For more information about the opportunity and application, please refer to the following link:https://www.google.com/about/careers/applications/jobs/results/76351911959110342
8 292
𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗝𝗼𝗯 𝗢𝗽𝗲𝗻𝗶𝗻𝗴𝘀 𝗜𝗻 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 😍
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8 292
Repost from Data Analyst Jobs
BCG is Hiring for DATA SCIENTIST
Role:- DATA SCIENTIST
Qualifications:- GRADUATION
Experience:- Fresher's and Experienced
Mode:- WORK FROM OFFICE
Apply Now:- https://careers.bcg.com/global/en/job/BCG1US26309EXTERNALENGLOBAL/Data-Scientist-India-BCG-X
👉WhatsApp Channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
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8 292
𝗚𝗲𝘁 𝗬𝗼𝘂𝗿 𝗗𝗿𝗲𝗮𝗺 𝗝𝗼𝗯 𝗜𝗻 𝗔𝗺𝗮𝘇𝗼𝗻, 𝗚𝗼𝗼𝗴𝗹𝗲, 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝗡𝗩𝗜𝗗𝗜𝗔, 𝗮𝗻𝗱 𝗠𝗲𝘁𝗮 (𝗙𝗮𝗰𝗲𝗯𝗼𝗼𝗸) 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲𝘀𝗲 𝗰𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀😍
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1. What is the Impact of Outliers on Logistic Regression?
The estimates of the Logistic Regression are sensitive to unusual observations such as outliers, high leverage, and influential observations. Therefore, to solve the problem of outliers, a sigmoid function is used in Logistic Regression.
2. What is the difference between vanilla RNNs and LSTMs?
The main difference between vanilla RNNs and LSTMs is that LSTMs are able to better remember long-term dependencies, while vanilla RNNs tend to forget them. This is due to the fact that LSTMs have a special type of memory cell that can retain information for longer periods of time, while vanilla RNNs only have a single layer of memory cells.
3. What is Masked Language Model in NLP?
Masked language models help learners to understand deep representations in downstream tasks by taking an output from the corrupt input. This model is often used to predict the words to be used in a sentence.
4. Why is the KNN Algorithm known as Lazy Learner?
When the KNN algorithm gets the training data, it does not learn and make a model, it just stores the data. Instead of finding any discriminative function with the help of the training data, it follows instance-based learning and also uses the training data when it actually needs to do some prediction on the unseen datasets. As a result, KNN does not immediately learn a model rather delays the learning thereby being referred to as Lazy Learner.
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𝟱 𝗙𝗥𝗘𝗘 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
Ready to dive into the world of Machine Learning? Here are 5 powerful resources that will guide you every step of the way—from beginner concepts to advanced techniques.
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8 292
AB InBev is hiring!
Position: Machine Learning Engineer
Qualification: Bachelor’s/ Master’s Degree
Salary: 12 - 20 LPA (Expected)
Experience: Freshers/ Experienced
Location: Work From Home/ office
📌Apply Now: https://ab-inbev-gcc.sensehq.com/careers/jobs/54769
8 292
Repost from Data Analyst Jobs
Citi is hiring!
Position: Data Scientist
Qualifications: Bachelor’s Degree
Salary: 12 - 18 LPA (Expected)
Experience: Freshers (0 - 2 Years)
Location: Bengaluru, India (Hybrid)
📌Apply Now: https://jobs.citi.com/job/-/-/287/76402677072
👉WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46
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8 292
𝗢𝗿𝗮𝗰𝗹𝗲 𝗦𝗤𝗟 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲😍
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8 292
SAP is Hiring for ASSOCIATE - DATA SCIENTIST"
Role:- ASSOCIATE - DATA SCIENTIST
Qualifications:- GRADUATION
Mode:- WORK FROM OFFICE
CTC:- 10 LPA
Location:- BANGALORE, KARNATAKA
Apply Now:- https://jobs.sap.com/job/Bangalore-Associate-Data-Scientist-KA-560066/1163936701/
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Are you looking to become a machine learning engineer?
I created a free and comprehensive roadmap. Let's go through this post and explore what you need to know to become an expert machine learning engineer:
Math & Statistics
Just like most other data roles, machine learning engineering starts with strong foundations from math, precisely linear algebra, probability and statistics.
Here are the probability units you will need to focus on:
Basic probability concepts statistics
Inferential statistics
Regression analysis
Experimental design and A/B testing Bayesian statistics
Calculus
Linear algebra
Python:
You can choose Python, R, Julia, or any other language, but Python is the most versatile and flexible language for machine learning.
Variables, data types, and basic operations
Control flow statements (e.g., if-else, loops)
Functions and modules
Error handling and exceptions
Basic data structures (e.g., lists, dictionaries, tuples)
Object-oriented programming concepts
Basic work with APIs
Detailed data structures and algorithmic thinking
Machine Learning Prerequisites:
Exploratory Data Analysis (EDA) with NumPy and Pandas
Basic data visualization techniques to visualize the variables and features.
Feature extraction
Feature engineering
Different types of encoding data
Machine Learning Fundamentals
Using scikit-learn library in combination with other Python libraries for:
Supervised Learning: (Linear Regression, K-Nearest Neighbors, Decision Trees)
Unsupervised Learning: (K-Means Clustering, Principal Component Analysis, Hierarchical Clustering)
Reinforcement Learning: (Q-Learning, Deep Q Network, Policy Gradients)
Solving two types of problems:
Regression
Classification
Neural Networks:
Neural networks are like computer brains that learn from examples, made up of layers of "neurons" that handle data. They learn without explicit instructions.
Types of Neural Networks:
Feedforward Neural Networks: Simplest form, with straight connections and no loops.
Convolutional Neural Networks (CNNs): Great for images, learning visual patterns.
Recurrent Neural Networks (RNNs): Good for sequences like text or time series, because they remember past information.
In Python, it’s the best to use TensorFlow and Keras libraries, as well as PyTorch, for deeper and more complex neural network systems.
Deep Learning:
Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled.
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Long Short-Term Memory Networks (LSTMs)
Generative Adversarial Networks (GANs)
Autoencoders
Deep Belief Networks (DBNs)
Transformer Models
Machine Learning Project Deployment
Machine learning engineers should also be able to dive into MLOps and project deployment. Here are the things that you should be familiar or skilled at:
Version Control for Data and Models
Automated Testing and Continuous Integration (CI)
Continuous Delivery and Deployment (CD)
Monitoring and Logging
Experiment Tracking and Management
Feature Stores
Data Pipeline and Workflow Orchestration
Infrastructure as Code (IaC)
Model Serving and APIs
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
Credits: https://t.me/datasciencefun
Like if you need similar content 😄👍
8 292
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀/𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗦𝘂𝗺𝗺𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝟮𝟬𝟮𝟱😍
Company Name:- Siemens Healthineers
Position: Data Analytics/Data Science Intern
Duration: 10-12 weeks
Start Dates: June 2nd or June 16th, 2025
Work Type: Hybrid (in-office & remote)
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