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Participated in
Janatahack: Cross-sell Prediction
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Participated in
HackLive 4: Guided Community Hackathon!
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Participated in
DataHour: Continuous Testing and Evaluation with LLMs
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Participated in
DataHour: Harnessing ML and NLP for Elevated Customer Experiences
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Participated in
Janatahack: Machine Learning in Agriculture
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Participated in
JanataHack: Recommendation Systems
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Participated in
LTFS Data Science FinHack 3
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Participated in
HackLive 3: Guided Hackathon - NLP
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Participated in
DataHour: Demystifying Demand Forecasting for Retail Success
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Participated in
DataHour: Unwritten Rules for Success in Machine Learning
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Participated in
DataHour: Why Did My AI Do That? Decoding Decision-Making in ML
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Participated in
DataHour: Machine Learning Tips and Tricks
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Participated in
Janatahack: Healthcare Analytics
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Participated in
Janatahack: Healthcare Analytics II
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Participated in
Janatahack: Independence Day 2020 ML Hackathon
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Participated in
Janatahack: Customer Segmentation
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Participated in
DataHour: From APIs to Insights: Building Custom Power BI Connectors for RESTful APIs
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Participated in
DataHour: Handling Satellite and Geospatial Raster Data in Python
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Participated in
DataHour: Titanic Machine Learning Case Study using Python
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Participated in
DataHour: Industrial Application of Large Language Models like ChatGPT
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Participated in
DataHour: Statistics with Python for Data Science
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Participated in
DataHour: Exploring Dimensionality Reduction
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Participated in
DataHour: Web Scraping using Python Libraries
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Participated in
DataHour: Introduction to Social Network Analysis
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Participated in
DataHour: Understanding Logistic Regression and Decision Tree Analysis
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Participated in
DataHour: Building an End-to-End Solution for Big Mart Sales Prediction
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Participated in
DataHour: Deep Dive into Kubernetes and Concepts of Containerization
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Participated in
DataHour: Unlocking Business Growth - The Power of Customer Segmentation
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Participated in
DataHour: An Introduction to Machine Learning with Sequence Data
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Participated in
DataHour: FIFA World Cup Match Analysis Using Python
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Participated in
DataHour: Personalizing Demand Planning Using Scenario Analysis
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Participated in
DataHour: Basics of Big Data File Formats
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Participated in
DataHour: ChatGPT and the Future of NLP Systems
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Participated in
DataHour: Getting Started with Python
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Participated in
DataHour: Generating Labeled Data through Weak Supervision
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Participated in
DataHour: Google Cloud Vertex AI Platform
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Participated in
DataHour: Apache Airflow - An Open Source Workflow Manager
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Participated in
DataHour: Data Availability Through Data Lake in Large Organization
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Participated in
DataHour: Feature Engineering and Selection for Machine Learning
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Participated in
DataHour: Best of Pandas & The Power of Simple Models
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Participated in
DataHour: Application of Data Science in Insurance Industry
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Participated in
DataHour: Caching in Data Science
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Participated in
DataHour: Machine Learning on Live Streaming Data for AIOps
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Participated in
DataHour: Evaluation Criteria for Validating Machine Learning Models
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Participated in
DataHour: Dataflow on Google Cloud
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Participated in
DataHour: Forecasting & Time-series Analysis
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Participated in
DataHour: Boosting Performance with Ensemble Methods
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Participated in
DataHour: How Companies Use SQL to Extract Meaningful Insights Through Data?
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Participated in
DataHour: Feature Engineering and benefits of EDA
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Participated in
DataHour: How Good is AI for Conversations?
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Participated in
DataHour: Constructing Machine Learning Pipelines using Scikit-learn
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Participated in
DataHour: Analyzing Data with SQL
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Participated in
DataHour: Building a Web Application using Flask
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Participated in
DataHour: Google Cloud No Code/Low Code AI Solutions
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Participated in
DataHour: Roadmap to Data Engineering for Beginners
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Participated in
DataHour: Data Architect vs Data Engineer
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Participated in
DataHour: Transforming HR with People Analytics
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Participated in
DataHour: Application of ML Classification Techniques in Banking Industry
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Participated in
DataHour: How to Forecast New Product Launches using Data Centric Approach
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Participated in
DataHour: Metrics in Tech - Using Data to Drive Business Decisions
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Participated in
DataHour: Deep Dive into Airflow Components
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Participated in
DataHour: Exploring the Best Book Sellers Dataset
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Participated in
DataHour: Solving Business Problems with Microsoft Excel
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Participated in
DataHour: Data Preparation and Feature Engineering in ML
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Participated in
DataHour: Unlocking the Power of Embeddings
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Participated in
DataHour: An Introduction to Spark for Data Engineering
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Participated in
DataHour: Optimizing Real-Time ML Inference with Nvidia Triton Inference Server
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Participated in
DataHour: A/B testing - Theory, Practice and Pitfalls
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Participated in
DataHour: Understanding Graph Data Science
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Participated in
DataHour: Dealing with Imbalanced Datasets in ML Classification Problems
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Participated in
DataHour: Salary Analysis and Prediction Using ML
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Participated in
DataHour: Data Wrangling Using Geospatial Data in Python
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Participated in
DataHour: Diabetic Patients’ Readmission Prediction using ML
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Participated in
DataHour: Making Data Pipelines Easy with Dataproc and Composer
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Participated in
DataHour: No-code ML Hands-on using Orange Data Mining Tool
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Participated in
DataHour: Deep Dive into Semantic Segmentation- Techniques, Challenges and State-of-the-Art
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Participated in
DataHour: Introduction to Docker
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Participated in
DataHour: Data Engineering - Tools and Techniques
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Participated in
DataHour: Build Apache Nifi using Serverless Cloud Infrastructure
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Participated in
DataHour: Data Engineering in a Nutshell
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Participated in
[Student DataFest 2018] Skilltest - Python for Data Science
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Participated in
Food Demand Forecasting
|
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Participated in
HR Analytics
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Participated in
Time Series Forecasting
|
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Participated in
2nd Global AI Conclave 2021
|
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Participated in
Webinar: Storytelling using Visualizations
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Participated in
Joke Rating Prediction
|
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Participated in
Twitter Sentiment Analysis
|
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Participated in
Practice Problem: Urban Sound Classification
|
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Participated in
Identify the apparels (Fashion MNIST)
|
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Participated in
Identify the Digits (MNIST)
|
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Participated in
JanataHack: Demand Forecasting
|
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Participated in
Data Science Blogathon III
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Participated in
Webinar: Need of Industry Exposure in learning and applying the practical aspects of Data Science
|
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Participated in
Share & Empower
|
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Participated in
Felicity : Kings of Machine Learning
|
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Participated in
Black Friday Sales Prediction
|
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Participated in
Big Mart Sales Prediction
|
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Participated in
Recommendation Engine
|
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Participated in
JanataHack: Machine Learning for Banking
|
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Participated in
HackLive 2 - Guided Community Hackathon!
|
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Participated in
Webinar: ML Model Building & Deployment
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Participated in
Loan Prediction
|
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Participated in
DataHour: Think like a Data Scientist
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Participated in
DataHour: SQL- One of the Key Ingredients for Data Science
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Participated in
DataHour: Data Science in a FAANG company!
|
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Participated in
DataHour: Introduction to Data-driven Decisions
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Participated in
DataHour: Effective Feature Engineering for Building Better Models
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Participated in
DataHour: Deploying Deep Learning model to production using FastAPI & Docker
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Participated in
DataHour: Improving Search Results with Semantic Search
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Participated in
DataHour: Artificial Intelligence in Retail
|
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Participated in
DataHour: Introduction to Network Science
|
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Participated in
DataHour: Build your first Chat-bot using Open Source Tools
|
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Participated in
DataHour: Traversing the Journey of an Analytics Problem
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Participated in
DataHour: Create Effective Data Science Notebooks and Communication
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Participated in
DataHour: How to transition into Data Science?
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Participated in
DataHour: Introduction to Blockchain
|
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Participated in
Football Hackathon
|
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Participated in
DataHour: Introduction to Image Processing using Python
|
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Participated in
DataHour: Efficient Implementations of Transformers
|
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Participated in
DataHour: Building Scalable, Secure and Responsible AI Solutions in Azure
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Participated in
DataHour: ML oops to MLOps!
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Participated in
DataHour: Writing Reusable and Reproducible Pipelines for Training Neural Networks
|
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Participated in
DataHour: Introduction to Tensorflow Javascript
|
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Participated in
DataHour: Introduction to MLOps
|
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Participated in
DataHour: Ask Kunal Anything About AI
|
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Participated in
DataHour: Causal Inference in Practice
|
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Participated in
DataHour: Introduction to Interpretable Machine Learning
|
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Participated in
DataHour: Data to Insightful Actions with No Code AI
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Participated in
DataHour: Building NLP applications using Hugging Face
|
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Participated in
Skill Test: Python for Data Science
|
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Participated in
DataHour: An Introduction and Hands-On to Named Entity Recognition
|
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Participated in
DataHour: Data Management and AI
|
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Participated in
DataHour: Hands-on with Social Network Analysis
|
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Participated in
Learn to Build an Artificial Intelligence Model with Kaggle Grandmasters
|
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Participated in
DataHour: Hands-on with Data Analysis Expressions(DAX) for Power BI
|
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Participated in
DataHour: Deep Learning - Maths Behind Back-Propagation
|
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Participated in
DataHour: Introduction to Optimization Problems for Data Scientists
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Participated in
DataHour: Everything you need to know about Speech Recognition
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Participated in
DataHour: Feature Engineering on Images using Convolutional Neural Networks(CNN)
|
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Participated in
DataHour: Building AI Applications in Minutes
|
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Participated in
DataHour: Real-world Applications of Data science
|
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Participated in
DataHour: Bias and Fairness in NLP
|
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Participated in
DataHour: Data Modeling Concepts
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Participated in
DataHour: Understanding Search Query
|
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Participated in
DataHour: Smart Machine Learning Solution Based on Ontology and Knowledge Graph
|
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Participated in
DataHour: Computer Vision Landscape
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Participated in
DataHour: Making Sense of Clinical Text Data at Scale with NLP
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Participated in
DataHour: Next Leap - Data Science Adoption to Application
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Participated in
DataHour: MLOps—DevOps for Machine Learning
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Participated in
DataHour: Analyzing Movie Data using MongoDB
|
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Participated in
DataHour: Designing an end-to-end Neural Search Pipeline with Similarity Learning
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Participated in
DataHour: Data Visualization using Python
|
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Participated in
DataHour: Understanding AWS Virtual Private Cloud(VPC) Concepts
|
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Participated in
DataHour: Introduction to Explainable AI (XAI)
|
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Participated in
DataHour: Leveraging GCP Vertex AI for Machine Learning
|
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Participated in
DataHour: Quantum Computing Simulator Acceleration
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Participated in
DataHour: Stirring up Data Science with SQL
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Participated in
DataHour: Methods for Explaining the Blackbox of Machine Learning Model
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Participated in
DataHour: Prediction to Production in Machine Learning
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Participated in
DataHour: Trees of Data Science
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Participated in
DataHour: Dynamic Time Warping for Time Series Classification
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Participated in
DataHour: Deep Dive into Practical Machine Learning with Career Insights
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Participated in
DataHour: Data Operations on Azure
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Participated in
DataHour: Jumpstart your Career with AWS AI/ML
|
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Participated in
DataHour: Nirvana State of MLOps
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Participated in
DataHour: Introduction to GAN - A Practical Approach
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Participated in
DataHour: Product Oriented Data Scientists
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Participated in
DataHour: Key steps for Designing Deep Neural Network and its scope in Industry
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Participated in
DataHour: Anomaly detection using NLP and Predictive Modeling
|
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Participated in
DataHour: Data Science in Retail
|
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Participated in
DataHour: Data Science Data management using Pandas
|
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Participated in
DataHour: Mitigating Bias in Machine Learning
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Participated in
DataHour: Google Cloud AI/ML
|
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Participated in
DataHour: Forecasting Stories
|
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Participated in
DataHour: Energy Data Science - Project From Scratch
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Participated in
DataHour: Getting Started with EDA tools - Numpy and Pandas
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Participated in
DataHour: Practical Applications of Data science in Ecommerce
|
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Participated in
DataHour: The Fundamentals of Quantum Computing
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Participated in
DataHour: Explainable AI - Need and Implementation
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Participated in
DataHour: How to tackle Overfitting?
|
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Participated in
DataHour: Hands-on with A/B Testing
|
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Participated in
DataHour: Key steps for Designing Artificial Neural Network (ANN) for Image classification
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Participated in
DataHour: Building Data Pipelines on GCP
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Participated in
DataHour: Modern Deep Learning Architecture
|
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Participated in
DataHour: An Introduction to AWS EMR
|
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Participated in
DataHour: 5 things you should know about Azure SQL
|
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Participated in
DataHour: Prediction to Production in Machine Learning
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Participated in
DataHour: Everything You Need to Know About Numpy
|
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Participated in
DataHour: Introduction To BigQuery ML
|
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Participated in
DataHour: AI & ML in the Automotive Industry
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Participated in
DataHour: ETL Pipelines in GCP
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Participated in
DataHour: Knowledge Graph Solutions using Neo4j
|
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Participated in
DataHour: Practical Time Series Analysis
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Participated in
DataHour: Building Machine Learning Models in BigQuery
|
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Participated in
DataHour: Getting Started with Big Data
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Participated in
DataHour: Key steps for Designing Convolutional Neural Network(CNN) for Image Classification
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Participated in
DataHour: An Introduction to Central Limit Theorem
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Participated in
DataHour: DCNN for Machine RUL Prediction using Time-series Data
|
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Participated in
DataHour: A Day in the Life of a Data Scientist
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Participated in
DataHour: Classification ML Model from Scratch
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Participated in
DataHour: NLP aspects in Telecommunication Industry
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Participated in
DataHour: Intelligent Knowledge Mining with Azure NLP and Graph databases
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Participated in
DataHour: Visualizing Data using Python
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Participated in
DataHour: Getting Started with AWS EC2
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Participated in
DataHour: Model Guesstimation (MLOps)
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Participated in
DataHour: An Unsupervised ML approach using Clustering
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Participated in
DataHour: ML Model Interpretation and Evaluation
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Participated in
DataHour: M in ML stands for Math & Magic
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Participated in
DataHour: Model Parameters vs Hyperparameters - Techniques in ML Engineering
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Participated in
DataHour: Customizing Large Language Models GPT3 for Real-life Use Cases
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Participated in
DataHour: Introduction to Federated Learning
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Participated in
DataHour: Extracting Value from Data
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Participated in
DataHour: AI in Banking
|
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Participated in
DataHour: When Airflow Meets Kubernetes - An Introduction to MLOps
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Participated in
DataHour: Data Engineering with Databricks
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Participated in
DataHour: Ensemble Techniques in Machine Learning
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Participated in
DataHour: Artificial Intelligence Approach in Stock Market Analysis
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Participated in
DataHour: An Introduction to Measuring Marketing Channel Effectiveness
|
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Participated in
DataHour: Everything You Need to Know About Pandas
|
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Participated in
DataHour: Building Effective Data Pipelines
|
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Participated in
DataHour: Data Science in Banking Industry
|
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Participated in
DataHour: Understanding Energy Industry through EDA
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Participated in
DataHour: Unfolding Model Evaluation Metrics in Machine Learning
|
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Participated in
DataHour: AI/ML Era in Customer Experience (CX)
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Participated in
DataHour: Introduction to Classification using Azure Machine Learning
|
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Participated in
DataHour: Hypothesis Testing A-Z
|
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Participated in
DataHour: Making AI work for Business
|
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Participated in
A Practical Approach to Kaggle Competition
|
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Participated in
DataHour: How to Approach an ML Problem Statement from Scratch
|
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Participated in
DataHour: Applications of Optimization in On-demand Food and Grocery Delivery
|
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Participated in
DataHour: Netflix Data Analysis using Python
|
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Participated in
DataHour: The Art of Feature Engineering
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Participated in
DataHour: Causal Experimentations - When A/B Test is Not Possible
|
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Participated in
DataHour: Introduction to Positive Unlabelled(PU) Learning
|
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Participated in
DataHour: Introduction and Hands-on workshop with Reinforcement Learning
|
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Participated in
DataHour: Customer Data Science Models - Retail and CPG
|
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Participated in
DataHour: Data Science Use Cases
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Participated in
DataHour: Need for Self Supervised Learning - Practice at SAP
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Participated in
DataHour: Using Data Science Methodology to Assess Equity in Communication
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Participated in
DataHour: Applications of Machine Learning in Self Driving Cars
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Participated in
DataHour: Diving into the field of Data Analytics
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Participated in
DataHour: How to start your Kaggle journey?
|
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Participated in
DataHour: Practical Hypothesis Testing
|
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Participated in
DataHour: Exploratory Data Analysis with F#
|
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Participated in
DataHour: Steps before using an ML Model
|
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Participated in
DataHour: Statistics in Data Science
|
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Participated in
DataHour: Understanding Dimensionality Reduction
|
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Participated in
DataHour: Data Science Use Cases - Part 2
|
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Participated in
DataHour: An Empathetic AI for Healthcare
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Participated in
DataHour: Data Warehouse and its importance in Data World
|
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Participated in
DataHour: HIV Analysis using ML and Flutter
|
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Participated in
DataHour: Churn Analytics in Telcos
|
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Participated in
DataHour: An Introduction to Extended Reality (XR)
|
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Participated in
DataHour: Predicting Road Quality using AI - An MLOps Demo Pipeline
|
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Participated in
DataHour: Python Data Structures
|
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Participated in
DataHour: Exploring Heart Disease Data using Python
|
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Participated in
DataHour: Evaluation Measures for Binary Classification
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Participated in
DataHour: SQL - Intermediate to Advanced
|
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Participated in
DataHour: Quantum Computing in Financial Industry
|
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Participated in
DataHour: Big Data Architecture and the Best Practices on AWS
|
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Participated in
DataHour: How Data Science is used in Fintech?
|
|
Participated in
DataHour: Introduction to Dimensional Data Modelling
|
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Participated in
DataHour: Advance SQL - Analytics/Windows Functions
|
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Participated in
DataHour: Building and Operationalizing an Explainable Predictive Model
|
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Participated in
DataHour: Importance of Statistics in Data Science and Machine Learning
|
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Participated in
DataHour: How do Algorithms Generate Recommendations?
|
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Participated in
DataHour: Classification Algorithms Evaluation Metrics
|
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Participated in
DataHour: Advanced Exploratory Data Analysis on Credit Data
|
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Participated in
DataHour: Exploring Multi-label & Multi-class Classification
|
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Participated in
DataHour: Normal Distribution - Understanding the Numbers and its Real Life Applications
|
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Participated in
DataHour: Cloud Dataproc - Migrate and Optimize Spark Workloads
|
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Participated in
DataHour: Building Cloud Native Data Pipelines
|
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Participated in
DataHour: Diabetes Prediction Using Survival Analysis
|
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Participated in
DataHour: Data Modelling Demystified
|
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Participated in
DataHour: Machine Learning Model Development using Pandas, Numpy and Scikit-Learn
|
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Participated in
DataHour: Analyzing Loan Application Data using Python
|
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Participated in
DataHour: Transforming Business Challenges into Data Driven Solution
|
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Participated in
DataHour: Hyperparameter Optimization Demystified
|
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Participated in
DataHour: Get Started with Hadoop
|
|
Participated in
DataHour: An Introduction to Apache Airflow
|
|
Participated in
DataHour: Introduction to Optimization using Genetic Algorithms
|
|
Participated in
DataHour: Understanding Logistic Regression
|
|
Participated in
DataHour: Anomaly Detection in Time Series Data
|
|
Participated in
DataHour: Real-time Machine Learning - Challenges and Solution
|
|
Participated in
DataHour: An Introduction to Big Data Processing using Apache Spark
|
|
Participated in
DataHour: Google BigQuery - The Modern Cloud Data Warehouse
|
|
Participated in
DataHour: Understanding ChatGPT and its Use Cases
|
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Participated in
DataHour: Experiments with Interpretable Artificial Intelligence
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Participated in
DataHour: Basic Concepts of Object Oriented Programming in Python
|
