💻 Strengthening Python fundamentals step by step! Practiced data structures and NumPy basics using Python in PyCharm, where I: ✅ Created and worked with Python Lists & Tuples ✅ Converted data into a NumPy Array ✅ Compared different data structures and their outputs Understanding these core concepts is helping me build a strong foundation for Data Analysis, Machine Learning, and AI. Small concepts today → Big skills tomorrow 🚀 #Python #NumPy #ProgrammingBasics #PyCharm #DataStructures #LearningJourney #StudentDeveloper #AI #DataScience
Strengthening Python Fundamentals with NumPy
More Relevant Posts
-
Developed a simple Linear Regression model to predict real estate values based on year data. This model was built using Python and deployed via a Flask API, enabling predictions through API requests. Tools used: • Python • Scikit-learn • Flask API • NumPy • Postman This project explores the integration of machine learning models into APIs for real-world prediction systems. It has been a valuable learning experience while experimenting with @Uptor. #MachineLearning #Python #FlaskAPI #DataScience #AI #Learning
To view or add a comment, sign in
-
🧠 Python + AI Quick Quiz Which Python library is most commonly used for Machine Learning? A) NumPy B) Pandas C) Scikit-learn D) Matplotlib 💬 Comment your answer below! I’ll share the correct answer in the comments tomorrow. #Python #MachineLearning #AI #DataScience #LearnPython
To view or add a comment, sign in
-
Exploring data analysis using Python in Google Colab 📊 Performed ANOVA test using pandas and statsmodels to understand the relationship between variables. Step by step learning, experimenting, and improving my data analytics skills every day. #Python #DataAnalysis #MachineLearning #Statistics #GoogleColab #LearningJourney #KPITBS #Coding
To view or add a comment, sign in
-
-
Hitting 'Play' on the Python journey again! ▶️🐍 After a brief pause from my daily updates, I am back at the keyboard and ready to dive deeper into code. Moving forward, my ultimate focus is building a strong foundation for Artificial Intelligence and Machine Learning. Mastering these core Python mechanics is step one on that roadmap, and I am excited to get the momentum going again. We are picking right back up where we left off. Day 7 is loading! 💻 Question for my network: For those of you working in data or AI, what core Python concept do you find yourself using the absolute most on a daily basis? 👇 #Python #MachineLearning #ArtificialIntelligence #LearningInPublic #100DaysOfCode
To view or add a comment, sign in
-
Python is the foundation of modern data science and a great place to start or strengthen your skills. From core syntax to loops, data structures, and working with external libraries, this Kaggle course builds practical Python knowledge step by step, and sets you up for machine learning, data analysis, and more. . #TFUGL #Kaggle #Python #DataScience #LearnToCode #CodingJourney #TechCommunity #MachineLearning #DeveloperSkills #Upskill #FreeCourses
To view or add a comment, sign in
-
-
Python is one of the most powerful languages for data science, thanks to its rich ecosystem of libraries that simplify data analysis and machine learning. Here are some essential libraries every data professional should know: #Python #DataScience #MachineLearning #AI #DeepLearning
To view or add a comment, sign in
-
-
🚀 Day 56/100 – Python, Data Analytics & Machine Learning Journey 🤖 Module 3: Machine Learning 📚 Today’s Learning: • Overfitting and underfitting Today, I focused on understanding overfitting and underfitting, two key challenges in building reliable machine learning models. I learned that underfitting occurs when a model is too simple and cannot capture the underlying patterns in the data, resulting in poor performance on both training and testing data. On the other hand, overfitting occurs when a model is too complex and memorizes the training data, including noise, which leads to high accuracy on training data but poor performance on unseen data. I also explored how model complexity directly impacts performance and why it is important to choose the right model and parameters. Understanding these concepts is essential for building robust models that perform well in real-world scenarios. The learning journey continues as I dive deeper into machine learning concepts 🚀 📌 Code & Notes: https://lnkd.in/dmFHqCrK #100DaysOfPython #MachineLearning #AIML #Python #LearningInPublic #DataScience 🚀
To view or add a comment, sign in
-
Check out the Statistics Globe Hub, an ongoing learning stream that helps you stay up to date with statistics, data science, AI, and programming using R and Python: https://lnkd.in/exBRgHh2 #RStats #python #datascience #Statistics #AI #statisticsglobehub
To view or add a comment, sign in
-
Check out the Statistics Globe Hub, an ongoing learning stream that helps you stay up to date with statistics, data science, AI, and programming using R and Python: https://lnkd.in/e5YB7k4d #RStats #python #datascience #Statistics #AI #statisticsglobehub
To view or add a comment, sign in
Explore related topics
Explore content categories
- Career
- Productivity
- Finance
- Soft Skills & Emotional Intelligence
- Project Management
- Education
- Technology
- Leadership
- Ecommerce
- User Experience
- Recruitment & HR
- Customer Experience
- Real Estate
- Marketing
- Sales
- Retail & Merchandising
- Science
- Supply Chain Management
- Future Of Work
- Consulting
- Writing
- Economics
- Artificial Intelligence
- Employee Experience
- Workplace Trends
- Fundraising
- Networking
- Corporate Social Responsibility
- Negotiation
- Communication
- Engineering
- Hospitality & Tourism
- Business Strategy
- Change Management
- Organizational Culture
- Design
- Innovation
- Event Planning
- Training & Development