Kumaran1987

Chatgpt driven Answers as below  Excellent question — you're thinking ahead like a true strategist. You want to reduce the team's working days to 4.5 days or even 3.5 days (without losing output) by using AI Automation + Agile Methods, right? This is very possible if you set up the system carefully. Let’s break it down practically: --- How to Achieve 4.5 or 3.5 Day Workweeks using AI + Agile --- Phase 1: Identify Automatable Activities (AI Scan) Run a simple audit: Goal: Cut down 30–40% of manual time-wasters. --- Phase 2: Adopt Agile Work Structuring Goal: Teams self-correct and accelerate without micro-management. --- Phase 3: Redesign Workflows with AI Assistance Agile AI Assistants: Deploy GPT-based assistants to: Write documentation drafts Generate test cases Propose user stories and acceptance criteria Predictive Monitoring: Use AI tools to detect risks in projects early (before they blow up). Examples: JIRA AI plugins, GitHub Copilot, Asana AI. --- Phase 4: Change the Wo...

Using Eisenhower Matrix (urgent-important matrix), STAR methods (for thinking through actions smartly) — a collection of efficient work strategies. full practical system for it: --- "5 Days into 2 Days" System (using prioritization + execution frameworks) --- 1. Prioritize Smartly — Eisenhower Matrix Every task you think you have → classify them into: Focus 80% of your time only on "Important" tasks. If you find yourself stuck doing "Not Important" — you're wasting energy. --- 2. Act Quickly — Use STAR Framework For every task, apply STAR thinking (like mini decision trees): Situation: What exactly needs to happen? (define it super clearly) Task: What is my specific responsibility? Action: What is the minimum effective action I can take? Result: What is the result I must deliver? This avoids overthinking — you focus only on "what matters" to move forward. --- 3. Batch and Time Block (90-30 Rule) 90 minutes → Deep Work 30 minutes → Break Repea...

Below is a Python implementation of a machine learning pipeline class that supports LightGBM , XGBoost , CatBoost , and AdaBoost , using RandomizedSearchCV to find the best hyperparameters. The output includes the best hyperparameters for each model in JSON format. Prerequisites Install required libraries: pip install lightgbm xgboost catboost scikit-learn pandas numpy Code: Machine Learning Pipeline Class import json import numpy as np from sklearn.model_selection import RandomizedSearchCV, train_test_split from sklearn.ensemble import AdaBoostClassifier from xgboost import XGBClassifier from lightgbm import LGBMClassifier from catboost import CatBoostClassifier from sklearn.metrics import accuracy_score class MLBoostPipeline: def __init__(self, random_state=42, n_iter=20, cv=5): self.random_state = random_state self.n_iter = n_iter self.cv = cv self.models = { "LightGBM": LGBMClassifier(random_state=self.r...

Below is a Python implementation of a machine learning pipeline class that supports LightGBM , XGBoost , CatBoost , and AdaBoost , using RandomizedSearchCV to find the best hyperparameters. The output includes the best hyperparameters for each model in JSON format. Prerequisites Install required libraries: pip install lightgbm xgboost catboost scikit-learn pandas numpy Code: Machine Learning Pipeline Class import json import numpy as np from sklearn.model_selection import RandomizedSearchCV, train_test_split from sklearn.ensemble import AdaBoostClassifier from xgboost import XGBClassifier from lightgbm import LGBMClassifier from catboost import CatBoostClassifier from sklearn.metrics import accuracy_score class MLBoostPipeline: def __init__(self, random_state=42, n_iter=20, cv=5): self.random_state = random_state self.n_iter = n_iter self.cv = cv self.models = { "LightGBM": LGBMClassifier(random_state=self.r...

Integrating Gemini AI API with LangChain AI agents allows you to create a more dynamic and intelligent data science pipeline. Below is an example of how to accomplish this: --- Steps to Integrate Gemini AI with LangChain 1. Set Up Gemini API: Use the Gemini AI API for specific tasks like preprocessing, training, and evaluating. 2. Define Tools: Use LangChain's Tool class to wrap Gemini API functions. 3. Create a LangChain Agent: The agent orchestrates the tools and interacts with the Gemini API. --- Python Code Prerequisites Install the required libraries: pip install langchain openai requests pandas Code import requests import pandas as pd from langchain.agents import initialize_agent, Tool from langchain.llms import OpenAI # Set your Gemini API key and endpoint API_KEY = "your_gemini_api_key" BASE_URL = "https://api.gemini.ai/v1" # Replace with actual Gemini API base URL # Define helper functions for the Gemini AI API def preprocess_data_gemini(da...

Senior Support Engineer Business Analyst Amazon Business Analyst Finance related Lead Data Engineer

Deep Dive into Business Analyst Specializing in Financial and Stock Market Analysis Here’s a comprehensive look into tools, certifications, and case studies relevant to this domain: --- 1. Tools for Financial and Stock Market Analysis Data Analysis and Visualization Python and R: Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn. Use Case: Data cleaning, predictive modeling, and machine learning for stock trend predictions. Power BI/Tableau: Use Case: Interactive dashboards for real-time market monitoring and KPI tracking. Microsoft Excel (Advanced): Use Case: Financial modeling, pivot tables, and Monte Carlo simulations. Market Analysis Platforms Bloomberg Terminal: Use Case: Real-time financial data, analytics, and news. Reuters Eikon: Use Case: Stock and commodity market analysis, trend monitoring. Yahoo Finance/Google Finance APIs: Use Case: Data retrieval for building custom stock dashboards. Databases and Querying Tools SQL: Use Case: Querying historical stock price dat...

Guidewire Architect CC Guidewire BA Guidewire QA

Multiple Guidewire openings Guidewire Architect Guidewire QA 5 to 12 Guidewire two job role openings

Java developer 3 to 5 Senior Data Scientist Business Analyst, Operations specialist Senior Manager