Nonchalant
4.1K posts
Nonchalant
@techyNonchalant
Breaking down tech & web dev into simple language | Learning in public 🚀
Under the Blue sky 가입일 Ocak 2026
436 팔로잉528 팔로워
Which AI tool do you think deserves way more hype right now? 👀
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@Sarthak4Alpha Make a video for beginners how to install it without “ making any mistake”
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Interviewer:
If apps like Instagram are free,
how do they store billions of photos and videos without charging users anything?
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Discord is a $15 billion dollar company ?????
Literally fifteen billion 😂😂😂😂😂😂😂
Dollors 🤣🤣🤣🤣🤣🤣🤣
and still has the worst app opening experience ever
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If you’re starting Machine Learning in 2026, don’t get lost in tutorials. Follow a roadmap that actually compounds:
(BookMark this 🔖)
Phase 1: Foundations (2–4 weeks)
- Python (lists, dicts, functions, OOP basics)
- Math (focus only what’s needed):
- Linear Algebra → vectors, matrices
- Probability → distributions, Bayes
- Calculus → gradients intuition
- Tools → NumPy, Pandas, Matplotlib
Phase 2: Core ML (4–6 weeks)
- Supervised Learning:
- Linear & Logistic Regression
- Decision Trees, Random Forest
- Unsupervised:
- K-Means, PCA
- Learn:
- Bias-Variance Tradeoff
- Overfitting, Cross-validation
- Implement models from scratch (this is where real understanding happens)
Phase 3: Practical ML (4–6 weeks)
- Scikit-learn (pipelines, preprocessing)
- Feature engineering
- Model evaluation (F1, ROC, confusion matrix)
- Work on datasets (Kaggle / UCI)
- Do 2–3 solid projects (not 10 half-baked ones)
Phase 4: Deep Learning (4–8 weeks)
- Neural Networks, Backpropagation
- Frameworks: PyTorch / TensorFlow
- CNNs (images), RNNs/Transformers (text)
- Build:
- Image classifier
- Text classifier
Phase 5: Specialization (ongoing)
Pick ONE based on interest:
- AI/LLMs → Transformers, RAG, fine-tuning
- Data Science → EDA, storytelling, dashboards
- MLOps → deployment, Docker, CI/CD
Phase 6: Real-World Edge
- Build end-to-end projects:
- Data → Model → API → UI
- Deploy (Streamlit / FastAPI)
- Learn basics of system design for ML
Golden Rules:
- Don’t just watch — build
- Don’t just build — deploy
- Don’t just deploy — explain
Consistency > intensity.
Most people quit in Phase 2.
If you reach Phase 5, you’re already ahead of 90%.
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@anantshah133 😂 “open source” changed the narrative real quick
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@code_bytein Still wondering 🤔 nobody said ChatGPT , anyway clean N simple answer
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