1. Home
  2. Detail

@disasters20804:

كوارث
كوارث
Open In TikTok:
Region: SD
Friday 25 September 2026 13:38:51 GMT
341
74
0
1

Music

Download

No Watermark .mp4 (0.39MB) No Watermark(HD) .mp4 (0.39MB) Watermark .mp4 (0MB) Music .mp3

Comments

There are no more comments for this video.
To see more videos from user @disasters20804, please go to the Tikwm homepage.

Other Videos

#nguoivanchuyen
#nguoivanchuyen
CHẤT LIỆU BẠN TRAI QUÁ CAPTAIN BOY ƠIII !!! #CAPTAINBOY #TCLC
CHẤT LIỆU BẠN TRAI QUÁ CAPTAIN BOY ƠIII !!! #CAPTAINBOY #TCLC
📊 DATA SCIENCE ROADMAP From Beginner to Job-Ready Data Scientist 🚀 Data Science isn’t just Python or Machine Learning. It’s the combination of data, statistics, programming, ML, and business thinking. 🟢 1. PYTHON 🐍 Master: • Variables & Data Types • Conditions & Loops • Functions • Data Structures • OOP Basics • NumPy • Pandas 🎯 Goal: Work confidently with data. 🔵 2. SQL 🗄️ Learn: • SELECT & Filtering • GROUP BY • JOINs • CASE WHEN • Subqueries • CTEs • Window Functions 🎯 Goal: Extract and analyze data from databases. 🟡 3. STATISTICS 📈 Understand: • Mean & Median • Variance & Standard Deviation • Probability • Distributions • Correlation • Hypothesis Testing • Confidence Intervals 🎯 Goal: Understand what the data actually means. 🟠 4. DATA ANALYSIS 🔍 Learn: • Data Cleaning • EDA • Feature Engineering • Visualization • Pattern Detection • Insight Generation Tools: 🐼 Pandas 📊 Matplotlib 📈 Seaborn 🔴 5. MACHINE LEARNING 🤖 Master the fundamentals: • Linear Regression • Logistic Regression • Decision Trees • Random Forest • Gradient Boosting • Clustering • Model Evaluation 🎯 Goal: Build models that solve real problems. 🟣 6. DEEP LEARNING 🧠 Then explore: • Neural Networks • CNNs • RNNs • Transformers • Computer Vision • NLP ⚫ 7. ML ENGINEERING 🚀 Learn how to take models beyond notebooks: • APIs • FastAPI • Docker • Git & GitHub • Cloud Deployment • Model Monitoring • MLOps 🎯 Goal: Build systems people can actually use. 🟢 8. GENERATIVE AI 🤖 Modern Data Scientists can also benefit from understanding: • LLMs • Embeddings • Vector Databases • RAG • AI Agents • LLM Evaluation 🗺️ THE COMPLETE PATH Python ⬇️ SQL ⬇️ Statistics ⬇️ Data Analysis ⬇️ Machine Learning ⬇️ Deep Learning ⬇️ ML Engineering ⬇️ Generative AI ⬇️ 🚀 Real-World Projects 💡 DON’T LEARN EVERYTHING AT ONCE Pick one layer. Learn → Practice → Build → Explain → Deploy Then move to the next. The goal isn’t to collect certificates or memorize algorithms. The goal is to become someone who can take: Raw Data → Analysis → Model → Insight → Solution 📌 Save this roadmap for your Data Science journey. #DataScience #DataScientist #DataAnalysis #creatorsearchinsights #datascience
📊 DATA SCIENCE ROADMAP From Beginner to Job-Ready Data Scientist 🚀 Data Science isn’t just Python or Machine Learning. It’s the combination of data, statistics, programming, ML, and business thinking. 🟢 1. PYTHON 🐍 Master: • Variables & Data Types • Conditions & Loops • Functions • Data Structures • OOP Basics • NumPy • Pandas 🎯 Goal: Work confidently with data. 🔵 2. SQL 🗄️ Learn: • SELECT & Filtering • GROUP BY • JOINs • CASE WHEN • Subqueries • CTEs • Window Functions 🎯 Goal: Extract and analyze data from databases. 🟡 3. STATISTICS 📈 Understand: • Mean & Median • Variance & Standard Deviation • Probability • Distributions • Correlation • Hypothesis Testing • Confidence Intervals 🎯 Goal: Understand what the data actually means. 🟠 4. DATA ANALYSIS 🔍 Learn: • Data Cleaning • EDA • Feature Engineering • Visualization • Pattern Detection • Insight Generation Tools: 🐼 Pandas 📊 Matplotlib 📈 Seaborn 🔴 5. MACHINE LEARNING 🤖 Master the fundamentals: • Linear Regression • Logistic Regression • Decision Trees • Random Forest • Gradient Boosting • Clustering • Model Evaluation 🎯 Goal: Build models that solve real problems. 🟣 6. DEEP LEARNING 🧠 Then explore: • Neural Networks • CNNs • RNNs • Transformers • Computer Vision • NLP ⚫ 7. ML ENGINEERING 🚀 Learn how to take models beyond notebooks: • APIs • FastAPI • Docker • Git & GitHub • Cloud Deployment • Model Monitoring • MLOps 🎯 Goal: Build systems people can actually use. 🟢 8. GENERATIVE AI 🤖 Modern Data Scientists can also benefit from understanding: • LLMs • Embeddings • Vector Databases • RAG • AI Agents • LLM Evaluation 🗺️ THE COMPLETE PATH Python ⬇️ SQL ⬇️ Statistics ⬇️ Data Analysis ⬇️ Machine Learning ⬇️ Deep Learning ⬇️ ML Engineering ⬇️ Generative AI ⬇️ 🚀 Real-World Projects 💡 DON’T LEARN EVERYTHING AT ONCE Pick one layer. Learn → Practice → Build → Explain → Deploy Then move to the next. The goal isn’t to collect certificates or memorize algorithms. The goal is to become someone who can take: Raw Data → Analysis → Model → Insight → Solution 📌 Save this roadmap for your Data Science journey. #DataScience #DataScientist #DataAnalysis #creatorsearchinsights #datascience
#meme #missasinfonia #clase #meme #fyp
#meme #missasinfonia #clase #meme #fyp




About

Legal