“The #Kaggle Workbook: Self-Learning Exercises and Valuable Insights for @Kaggle #DataScience Competitions": http://
amzn.to/41jKa7r by @tng_konrad and @LucaMassaron ——————
#Analytics #DataScientist #AI #DeepLearning #ML #MachineLearning #Python #Coding
DATA
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Kaggle Workbook: Self-Learning Exercises for Data Science Competitions
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The Data Science Design Manual: Essential Resource for Data Scientists
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The Data Science Design Manual: http://
amzn.to/45lXMTn
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#DataScience #DataScientist #Analytics #AI #ML #MachineLearning #DataViz #DataStorytelling #DataLiteracy -
Machine Learning and Generative AI for Marketing with Python
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#MachineLearning and #GenerativeAI for Marketing using #Python — http://
amzn.to/4dNES9Z via @PacktDataML Key Features: Enhance customer engagement and personalization through predictive analytics and advanced segmentation techniques Combine Python programming with the -
Master Trending AI Tech in 2025 – Complete Learning Roadmap
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Master Trending AI Tech in 2025 – Roadmap Fundamentals (1–1.5 mo) Python | Data Analysis | Math for AI | Git | Cloud Basics Core Machine Learning (1.5–2 mo) Supervised/Unsupervised | Pipelines | Model Monitoring | Feature Eng. Deep
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AI Automation: 15-20% Work Tasks with DeepAgent
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AI can automate about 15-20% of your work. Today, AI can:
•Read and write docs
•Analyze data and generate reports
•Connect systems and automate workflows
•Handle emails and schedule meetings
•Listen to calls and help answer questions You can try these out with DeepAgent: -
Deploying Optimized AI Agents Across Business Units
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Once optimized with data, these AI agents can be deployed across business units.
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Feed Agents Consistent Relevant Data for Smarter Operations
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Feeding your agent a consistent stream of relevant data helps them operate smarter.
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Agents Excel at Automation with Clear Data Strategy
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Agents excel at automation with a clear data strategy.
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2TB simulation data rediscovers equations efficiently
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Wow! It only takes 2 TB of simulation data to rediscover a few equations!
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Closing the Robot Data Gap Discussion at NYU
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Looking fwd to discussing how to close the massive “Robot Data Gap” tomorrow at 11am @nyuniversity
: https://
cs.nyu.edu/dynamic/about/
news/colloquium/1381/
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