Deep Learning Notes

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Mayelana nalolu hlelo lokusebenza

📘 Amanothi Okufunda Okujulile (Inguqulo ka-2025–2026)

📚 I-Deep Learning Notes (2025–2026) Edition iyisisetshenziswa esiphelele sezemfundo nesisebenzayo esiklanyelwe izitshudeni zasenyuvesi, abafundi basekolishi, iziqu zobunjiniyela besofthiwe, kanye nonjiniyela abasafufusa. Ihlanganisa yonke isilabhasi yokufunda ejulile ngendlela ehlelekile nelungele abafundi, lolu hlobo luhlanganisa isilabhasi ephelele nama-MCQ wokuzijwayeza kanye nemibuzo ukuze yenze ukufunda kusebenze futhi kuhehe.

Lolu hlelo lokusebenza luhlinzeka ngomhlahlandlela wesinyathelo ngesinyathelo ukuze ukwazi imiqondo yokufunda ejulile, kusukela kweziyisisekelo zokuhlela nokuqhubekela kuzihloko ezithuthukile ezifana namanethiwekhi okuxhumana, amanethiwekhi emizwa ajwayelekile, namamodeli angenzeka ahlelekile. Iyunithi ngayinye iklanywe ngokucophelela ngezincazelo, izibonelo, nemibuzo yokuzijwayeza ukuqinisa ukuqonda nokulungiselela abafundi izivivinyo zemfundo kanye nokuthuthuka kochwepheshe.

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🎯 Imiphumela yokufunda:

- Qonda imiqondo yokufunda ejulile kusukela kokuyisisekelo kuya ezinhlelweni ezithuthukile.
- Qinisa ulwazi ngama-MCQ ahlakaniphile kanye nemibuzo.
- Thola isipiliyoni sokusebenzisa amakhodi.
- Lungiselela ngempumelelo izivivinyo zasenyuvesi kanye nezingxoxo zobuchwepheshe.

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📂 Amayunithi Nezihloko

🔹 Iyunithi 1: Isingeniso Sokufunda Okujulile
- Kuyini Ukufunda Okujulile?
- Amathrendi Omlando
- Izindaba Ezijulile Zempumelelo Yokufunda

🔹 Iyunithi 2: I-Algebra Ewumugqa
- Scalars, Vectors, Matrices, futhi Tensors
- Ukuphindaphinda kwe-Matrix
- Eigendecomposition
- Ukuhlaziywa Kwezingxenye Eziyinhloko

🔹 Iyunithi 3: Amathuba kanye Nethiyori Yolwazi
- Amathuba Okusatshalaliswa
- Amathuba Aseceleni Nemibandela
- Umthetho we-Bayes
- I-Entropy ne-KL Divergence

🔹 Iyunithi 4: Ukubala Ngezinombolo
- Ukuchichima nokugeleza kancane
- Ukuthuthukisa Okususelwe Kwi-Gradient
- Ukuthuthukisa Okuphoqelekile
- Umehluko ozenzakalelayo

🔹 Iyunithi 5: Izisekelo Zokufunda Ngomshini
- Ukufunda ama-algorithms
- Amandla kanye nokufakwa ngokweqile kanye nokungafanelekile

🔹 Iyunithi 6: Amanethiwekhi Okudlulisa Okujulile
- Izakhiwo zeNeural Networks
- Ukuqalisa Imisebenzi
- Universal Approximation
- Ukujula vs. Ububanzi

🔹 Iyunithi 7: Ukuhlelwa kabusha Kokufunda Okujulile
- L1 kanye L2 Regularization
- Shiya phansi
- Ukuma Kwangaphambi kwesikhathi
- Data Augmentation

🔹 Iyunithi 8: Ukulungiselela Amamodeli Ajulile Wokuqeqesha
- I-Gradient Descent Variants
- Umfutho
- Amazinga Okufunda Aguquguqukayo
- Izinselele Kokuthuthukisa

🔹 Iyunithi 9: Amanethiwekhi Okuguqula
- Ukusebenza kwe-Convolution
- Izendlalelo zokuhlanganisa
- CNN Architectures
- Izicelo Embonweni

🔹 Iyunithi 10: Ukulingisa Ukulandelana: Amanethi Aphindaphindayo Naphindaphindayo
- Amanethiwekhi E-Neural Ajwayelekile
- Inkumbulo Yesikhathi Esifushane Eside
- I-GRU
- I-Recursive Neural Networks

🔹 Iyunithi 11: Indlela Esebenzayo
- Ukulinganisa Ukusebenza
- Amasu okulungisa iphutha
- Ukuthuthukiswa kwe-hyperparameter
- Dlulisa Ukufunda

🔹 Iyunithi 12: Izicelo
- Computer Vision
- Ukuqashelwa Inkulumo
- Ukucubungula Ulimi Lwemvelo
- Ukudlala umdlalo

🔹 Iyunithi 13: Amamodeli Akhiqiza Ajulile
- Ama-autoencoder
- Ama-Autoencoder ahlukahlukene
- Imishini ye-Boltzmann Ekhawulelwe
- Generative Adversarial Networks

🔹 Iyunithi 14: Amamodeli E-Linear Factor
- PCA kanye Factor Analysis
- I-ICA
- Ukubhala ngekhodi okuncane
- I-Matrix Factorization

🔹 Iyunithi 15: Ama-autoencoder
- Ama-Autoencoder ayisisekelo
- I-Denoising Autoencoder
- Ama-autoencoder anenkontileka
- Ama-Autoencoder ahlukahlukene

🔹 Iyunithi 16: Ukufunda Ngokumele
- Izethulo Sabalalisiwe
- Ukufunda Okuningi
- Deep Belief Networks
- Pretraining Techniques

🔹 Iyunithi 17: Amamodeli Angahle Akhiwe Okufunda Okujulile
- Amamodeli Ezithombe Aqondisiwe Nangaqondile
- Incazelo elinganiselwe
- Ukufunda ngezinguquko ezifihlekile

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🌟 Kungani Khetha Lolu hlelo lokusebenza?
- Ihlanganisa isilabhasi yokufunda ejulile ngefomethi ehlelekile enama-MCQ, nemibuzo yokuzijwayeza.
- Ifanele i-BS/CS, BS/IT, izitshudeni zobunjiniyela besofthiwe, nabathuthukisi.
- Yakha izisekelo eziqinile ekuxazululeni izinkinga kanye nezinhlelo zochwepheshe.

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✍ Lolu hlelo lokusebenza liphefumulelwe ababhali:
Ian Goodfellow, Yoshua Bengio, Aaron Courville

📥 Landa Manje!
Thola i-Deep Learning Notes (2025–2026) Edition namuhla! Funda, uzijwayeze, futhi ufundise imiqondo ejulile yokufunda ngendlela ehlelekile, egxile ezivivinyweni, nangendlela yobungcweti.

Yini entsha

🚀 Initial Launch of Deep Learning Notes

✨ What’s Inside:
✅ Complete syllabus covering deep learning fundamentals
✅ Interactive MCQs & quizzes for self-assessment
✅ Perfect for students & developers who want to master the subject

🎯 Suitable For:
👩‍🎓 Students of BSCS, BSIT, Software Engineering & ICS
📘 University & college exams (CS/IT related subjects)
🏆 Test prep for certifications & technical assessments
💻 Beginners aiming for freelancing & entry-level developer jobs