Forwarded from AI Jobs (Artificial Intelligence)
Hiring for Data scientist & analyst
➡️Experience : 2yrs to 6yrs (minimum 2 years of relevant skills)
➡️Role : Contractual (6 months to 12months) (min-6months)
✅Work from home
Mandatory skills: Python & Data science skills
✅Salary : $15 to $21 per hour
(year gap & career gap is also accepted)
Last date to apply 20th April-2024
Click on below link to apply for this role
👇👇👇👇
https://api.whatsapp.com/send?phone=918660785310&text=I%20want%20to%20apply%20for%20Data%20science%20role
➡️Experience : 2yrs to 6yrs (minimum 2 years of relevant skills)
➡️Role : Contractual (6 months to 12months) (min-6months)
✅Work from home
Mandatory skills: Python & Data science skills
✅Salary : $15 to $21 per hour
(year gap & career gap is also accepted)
Last date to apply 20th April-2024
Click on below link to apply for this role
👇👇👇👇
https://api.whatsapp.com/send?phone=918660785310&text=I%20want%20to%20apply%20for%20Data%20science%20role
WhatsApp.com
Ankita jain~Managing director
Business Account
❤2
Null Handling Functions in SQL:
1. ISNULL():
When there is a requirement for quick fix of null values, ISNULL() functions replaces NULL with a specified alternative value. This function is ideal for scenarios where we want a straightforward substitution for a single value.
Example:
SELECT order_id,city, isnull(city,'unknown') as new_city
FROM orders;
In this query, if "city" is NULL, 'unknown' is returned instead.
2.COALESCE():
COALESCE() returns the first non-null expression among its arguments. It's versatile than ISNULL(), allowing multiple inputs.
Example:
SELECT order_id, city, coalesce(city,state,region,'unknown') as new_city
FROM orders;
In this query, if "city" is not null, it will be returned. If "city" is null, it checks "state", then "region". If all three are null, it returns 'unknown'.
1. ISNULL():
When there is a requirement for quick fix of null values, ISNULL() functions replaces NULL with a specified alternative value. This function is ideal for scenarios where we want a straightforward substitution for a single value.
Example:
SELECT order_id,city, isnull(city,'unknown') as new_city
FROM orders;
In this query, if "city" is NULL, 'unknown' is returned instead.
2.COALESCE():
COALESCE() returns the first non-null expression among its arguments. It's versatile than ISNULL(), allowing multiple inputs.
Example:
SELECT order_id, city, coalesce(city,state,region,'unknown') as new_city
FROM orders;
In this query, if "city" is not null, it will be returned. If "city" is null, it checks "state", then "region". If all three are null, it returns 'unknown'.
We’re assembling the founding team and are looking for an ML Engineer/Data Scientist with experience building Search & Recommendation systems. You will work closely with the founders to bring this vision to reality. Ping me in case you are up for a challenging opportunity and be part of a team that's making waves in the tech industry
Please send your resume to - sonam@anzyglobal.com
Please send your resume to - sonam@anzyglobal.com
Some common Data Structures and Algorithms (DSA) questions that are often asked in Amazon interviews for the Software Development Engineer (SDE-1) role:
1. Arrays and Strings:
- Find the longest substring without repeating characters.
- Rotate an array to the right by k steps.
- Implement a function to perform string compression using counts of repeated characters.
2. Linked Lists:
- Reverse a linked list.
- Detect a cycle in a linked list.
- Merge two sorted linked lists.
3. Stacks and Queues:
- Implement a queue using two stacks.
- Evaluate a postfix expression.
- Design a stack that supports push, pop, top, and retrieving the minimum element in constant time.
4. Trees and Graphs:
- Check if a binary tree is a valid binary search tree (BST).
- Find the lowest common ancestor (LCA) of two nodes in a binary tree.
- Implement a graph traversal algorithm (BFS or DFS).
5. Sorting and Searching:
- Implement the quicksort or mergesort algorithm.
- Find the kth largest element in an array.
- Search for a given value in a sorted and rotated array.
6. Dynamic Programming:
- Find the maximum subarray sum.
- Count the number of unique paths in a grid.
- Longest increasing subsequence.
7. Design Problems:
- Design a Least Recently Used (LRU) cache.
- Design a data structure that supports insert, delete, get random element operations in constant time.
- Implement a trie (prefix tree) for efficient word insertions and searches.
8. Bit Manipulation:
- Count the number of set bits in an integer.
- Find the single non-repeated element in an array where every other element appears twice.
- Reverse the bits of a given integer.
1. Arrays and Strings:
- Find the longest substring without repeating characters.
- Rotate an array to the right by k steps.
- Implement a function to perform string compression using counts of repeated characters.
2. Linked Lists:
- Reverse a linked list.
- Detect a cycle in a linked list.
- Merge two sorted linked lists.
3. Stacks and Queues:
- Implement a queue using two stacks.
- Evaluate a postfix expression.
- Design a stack that supports push, pop, top, and retrieving the minimum element in constant time.
4. Trees and Graphs:
- Check if a binary tree is a valid binary search tree (BST).
- Find the lowest common ancestor (LCA) of two nodes in a binary tree.
- Implement a graph traversal algorithm (BFS or DFS).
5. Sorting and Searching:
- Implement the quicksort or mergesort algorithm.
- Find the kth largest element in an array.
- Search for a given value in a sorted and rotated array.
6. Dynamic Programming:
- Find the maximum subarray sum.
- Count the number of unique paths in a grid.
- Longest increasing subsequence.
7. Design Problems:
- Design a Least Recently Used (LRU) cache.
- Design a data structure that supports insert, delete, get random element operations in constant time.
- Implement a trie (prefix tree) for efficient word insertions and searches.
8. Bit Manipulation:
- Count the number of set bits in an integer.
- Find the single non-repeated element in an array where every other element appears twice.
- Reverse the bits of a given integer.
We are currently seeking a Data Scientist/Senior Data Scientist based in Bangalore with 2-6 years of experience in the field. The ideal candidate will demonstrate proficiency in Machine Learning, Deep Learning, and Natural Language Processing, coupled with robust coding abilities in Python.
additionally, should have prior experience working with text-based data and possess strong Probability & Statistics skills. Preference will be given to candidates available for immediate joining. If you meet these qualifications, we encourage you to reach out to us
📝 To Apply: Please submit your resume to harish.kumar@foundit.ai or reach out to us via WhatsApp at +91 9999062037.
additionally, should have prior experience working with text-based data and possess strong Probability & Statistics skills. Preference will be given to candidates available for immediate joining. If you meet these qualifications, we encourage you to reach out to us
📝 To Apply: Please submit your resume to harish.kumar@foundit.ai or reach out to us via WhatsApp at +91 9999062037.
Forwarded from Machine Learning And AI
YouTube
Stroke Prediction using Machine Learning Algorithms!! Train and Test.
Visit geekycodes.in for more datascience blogs. In this tutorial, we'll learn how to predict Stroke using Stroke Data. We'll also learn how to avoid common issues that make most stock price models overfit in the real world.
I have downloaded data from kaggle…
I have downloaded data from kaggle…
❤1
XGBoost: A Comprehensive Tutorial – Geeky Codes
https://geekycodes.in/xgboost-a-comprehensive-tutorial/
https://geekycodes.in/xgboost-a-comprehensive-tutorial/
Geeky Codes
XGBoost: A Comprehensive Tutorial
Introduction: In the realm of machine learning algorithms, XGBoost stands tall as a powerhouse, renowned for its efficiency, effectiveness, and versatility. This tutorial aims to provide a thorough…