
Agha Ali Raza - Youtube Channel
@aghaaliraza

![[Generative AI in Urdu/Hindi] Lecture 18: Positional encodings](https://i.ytimg.com/vi/5ElJUeInD5g/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 18: Positional encodings
[IA générative en ourdou/hindi] Leçon 18 : Encodages positionnels
![[Generative AI in Urdu/Hindi] Lecture 17: Transformers (first pass)](https://i.ytimg.com/vi/-FEuUtT_T_E/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 17: Transformers (first pass)
[IA générative en ourdou/hindi] Leçon 17 : Transformers (premier passage)
![[Generative AI in Urdu/Hindi] Lecture 16: attention, drawbacks of RNN & LSTM, intro. to transformers](https://i.ytimg.com/vi/5Z11FbrWswk/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 16: attention, drawbacks of RNN & LSTM, intro. to transformers
[IA générative en ourdou/hindi] Leçon 16 : attention, inconvénients de RNN et LSTM, introduction aux transformers
![[Generative AI in Urdu/Hindi] Lecture 15: Methods of computing attention](https://i.ytimg.com/vi/s82WGvA8MMg/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 15: Methods of computing attention
[IA générative en ourdou/hindi] Conférence 15 : Méthodes de calcul de l'attention
![[Generative AI in Urdu/Hindi] Lecture 14: Conditional language models, encoder-decoder, attention.](https://i.ytimg.com/vi/Q2cPX96n7is/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 14: Conditional language models, encoder-decoder, attention.
[IA générative en ourdou/hindi] Conférence 14 : Modèles de langage conditionnels, encodeur-décodeur, attention.
![[Generative AI in Urdu/Hindi] Lecture 13: LSTMs, bi-directional, multi-layer, teacher forcing.](https://i.ytimg.com/vi/w8ifNHyUVxI/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 13: LSTMs, bi-directional, multi-layer, teacher forcing.
[IA générative en ourdou/hindi] Leçon 13 : LSTM, bidirectionnel, multicouche, forçage par enseignant.
![[Generative AI in Urdu/Hindi] Lecture 12: RNN variations, its issues, possible solutions. LSTMs.](https://i.ytimg.com/vi/aQRcM6g_mJw/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 12: RNN variations, its issues, possible solutions. LSTMs.
[IA générative en ourdou/hindi] Leçon 12 : Variations de RNN, ses problèmes, solutions possibles. LSTM.
![[Generative AI in Urdu/Hindi] Lecture 11: RNNs training, derivations, applications and more!](https://i.ytimg.com/vi/xvFnn_dDJK0/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 11: RNNs training, derivations, applications and more!
[IA générative en ourdou/hindi] Leçon 11 : Entraînement des RNN, dérivations, applications et plus !
![[Generative AI in Urdu/Hindi] Lecture 10: Feed-forward NNs, pooling layer, sequence modelling, RNNs](https://i.ytimg.com/vi/INcVmFLzpU4/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 10: Feed-forward NNs, pooling layer, sequence modelling, RNNs
[IA générative en ourdou/hindi] Leçon 10 : Réseaux de neurones feed-forward, couche de pooling, modélisation de séquences, RNN
![[Generative AI in Urdu/Hindi] Lecture 9: Developing a complete feed-forward neural network](https://i.ytimg.com/vi/JjeDSKMTJdw/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 9: Developing a complete feed-forward neural network
[IA générative en ourdou/hindi] Leçon 9 : Développer un réseau neuronal feed-forward complet
![[Generative AI in Urdu/Hindi] Lecture 8: Embeddings: maths, negative sampling, best practices, bias](https://i.ytimg.com/vi/KVb15f8RWjI/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 8: Embeddings: maths, negative sampling, best practices, bias
[IA générative en ourdou/hindi] Leçon 8 : Plongements : mathématiques, échantillonnage négatif, bonnes pratiques, biais
![[Generative AI in Urdu/Hindi] Lecture 7: Embeddings (cont.) - Word2vec, Skipgram, CBOW](https://i.ytimg.com/vi/NNHDsSmJbic/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 7: Embeddings (cont.) - Word2vec, Skipgram, CBOW
[IA générative en ourdou/hindi] Leçon 7 : Embeddings (suite) - Word2vec, Skipgram, CBOW
![[Generative AI in Urdu/Hindi] Lecture 6: Embeddings – Word formations, ambiguity, vectorization](https://i.ytimg.com/vi/lQUgj8t1lsc/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 6: Embeddings – Word formations, ambiguity, vectorization
[IA générative en ourdou/hindi] Leçon 6 : Embeddings – Formations de mots, ambiguïté, vectorisation
![[Generative AI in Urdu/Hindi] Lecture 5: Tokenization (cont.) – algorithms, examples, best practices](https://i.ytimg.com/vi/pRBDh1zj9nQ/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 5: Tokenization (cont.) – algorithms, examples, best practices
[IA générative en ourdou/hindi] Leçon 5 : Tokenisation (suite) – algorithmes, exemples, bonnes pratiques
![[Generative AI in Urdu/Hindi] Lecture 4: Tokenization – concept, types, their problems, solutions](https://i.ytimg.com/vi/VYGzh23q7n4/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 4: Tokenization – concept, types, their problems, solutions
[IA générative en ourdou/hindi] Leçon 4 : Tokenisation – concept, types, leurs problèmes, solutions
![[Generative AI in Urdu/Hindi] Lecture 3: Language - embeddings to encoding, modelling to fine-tuning](https://i.ytimg.com/vi/IUGf8e3uEfo/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 3: Language - embeddings to encoding, modelling to fine-tuning
[IA générative en ourdou/hindi] Conférence 3 : Langage - des embeddings à l'encodage, de la modélisation au fine-tuning
![[Generative AI in Urdu/Hindi] Lecture 2: Language – concepts to terminologies, vectors to embeddings](https://i.ytimg.com/vi/RkqRDK7h7po/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 2: Language – concepts to terminologies, vectors to embeddings
[IA générative en ourdou/hindi] Leçon 2: Langue – des concepts à la terminologie, des vecteurs aux embeddings
![[Generative AI in Urdu/Hindi] Lecture 1: Course expectations, objectives and contents](https://i.ytimg.com/vi/g9FIL-ZtIkE/maxresdefault.jpg)
[Generative AI in Urdu/Hindi] Lecture 1: Course expectations, objectives and contents
[IA générative en ourdou/hindi] Cours 1 : Attentes, objectifs et contenus du cours