Makeesy AI

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Using the channel, we'll try to understand the AI concepts with basic implementations. The Idea would be to explain a single topic in a simple and short video.

Makeesy AI, Let's Keep It Simple.

Created by Raj Nath Patel - https://patelrajnath.github.io/
I'm a Research Scientist and working mainly in NLP domain. I create these tutorials aiming to give Basic AI Tools to more-and-more people.

Feel free to contact me via Email/YouTube Comments/Facebook/LinkedIn/Twitter.

Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.

Pytorch for Beginners #43 | Transformer Model: Implement EncoderDecoder
Pytorch for Beginners #43 | Transformer Model: Implement EncoderDecoder
Pytorch for Beginners #42 | Transformer Model: Implement Decoder
Pytorch for Beginners #42 | Transformer Model: Implement Decoder
Pytorch for Beginners #41 | Transformer Model: Implement Encoder
Pytorch for Beginners #41 | Transformer Model: Implement Encoder
Pytorch for Beginners #40 | Transformer Model: Understanding LayerNorm with in-depth-details
Pytorch for Beginners #40 | Transformer Model: Understanding LayerNorm with in-depth-details
Pytorch for Beginners #39 | Transformer Model: Understanding BatchNorm with in-depth-details
Pytorch for Beginners #39 | Transformer Model: Understanding BatchNorm with in-depth-details
Pytorch for Beginners #38 | Transformer Model: Understanding Dropout with In-Depth-Details
Pytorch for Beginners #38 | Transformer Model: Understanding Dropout with In-Depth-Details
Pytorch for Beginners #37 | Transformer Model: Masked SelfAttention - Implementation
Pytorch for Beginners #37 | Transformer Model: Masked SelfAttention - Implementation
Pytorch for Beginners #36 | Transformer Model: Decoder Attention Masking
Pytorch for Beginners #36 | Transformer Model: Decoder Attention Masking
Pytorch for Beginners #35 | Transformer Model: Encoder Attention Masking
Pytorch for Beginners #35 | Transformer Model: Encoder Attention Masking
Pytorch for Beginners #34 | Transformer Model: Understand Masking
Pytorch for Beginners #34 | Transformer Model: Understand Masking
Pytorch for Beginners #33 | Transformer Model: Position Embeddings- Validate Properties - Part 2
Pytorch for Beginners #33 | Transformer Model: Position Embeddings- Validate Properties - Part 2
Pytorch for Beginners #32 | Transformer Model: Position Embeddings - Validate Properties
Pytorch for Beginners #32 | Transformer Model: Position Embeddings - Validate Properties
Pytorch for Beginners #31 | Transformer Model: Position Embeddings - Implement and Visualize
Pytorch for Beginners #31 | Transformer Model: Position Embeddings - Implement and Visualize
Pytorch for Beginners #30 | Transformer Model - Position Embeddings
Pytorch for Beginners #30 | Transformer Model - Position Embeddings
Pytorch for Beginners #29 | Transformer Model: Multiheaded Attention - Scaled Dot-Product
Pytorch for Beginners #29 | Transformer Model: Multiheaded Attention - Scaled Dot-Product
Pytorch for Beginners #28 | Transformer Model: Multiheaded Attention - Optimize Basic Implementation
Pytorch for Beginners #28 | Transformer Model: Multiheaded Attention - Optimize Basic Implementation
Pytorch for Beginners #27 | Transformer Model: Multiheaded Attn-Implementation with In-Depth-Details
Pytorch for Beginners #27 | Transformer Model: Multiheaded Attn-Implementation with In-Depth-Details
Pytorch for Beginners #26 | Transformer Model: Self Attention - Optimize Basic Implementation
Pytorch for Beginners #26 | Transformer Model: Self Attention - Optimize Basic Implementation
Pytorch for Beginners #25 | Transformer Model: Self Attention - Implementation with In-Depth Details
Pytorch for Beginners #25 | Transformer Model: Self Attention - Implementation with In-Depth Details
Pytorch for Beginners #24 | Transformer Model: Self Attention - Simplest Explanation
Pytorch for Beginners #24 | Transformer Model: Self Attention - Simplest Explanation
Pytorch for Beginners #23 | Recurrent Neural Networks: Understanding and Implementing GRU
Pytorch for Beginners #23 | Recurrent Neural Networks: Understanding and Implementing GRU
Pytorch for Beginners #22 | Recurrent Neural Networks: Understanding and Implementing LSTM
Pytorch for Beginners #22 | Recurrent Neural Networks: Understanding and Implementing LSTM
Pytorch for Beginners #21 | Recurrent Neural Networks: Understanding and Implementing Vanilla RNN
Pytorch for Beginners #21 | Recurrent Neural Networks: Understanding and Implementing Vanilla RNN
Pytorch for Beginners #20 | Optimizers: SGD with Manual Gradient Computation
Pytorch for Beginners #20 | Optimizers: SGD with Manual Gradient Computation
Pytorch for Beginners #19 | Optimizers: Stochastic Gradient Descent and Adaptive Moment Estimation
Pytorch for Beginners #19 | Optimizers: Stochastic Gradient Descent and Adaptive Moment Estimation
Pytorch for Beginners #18 | Loss Functions: Ranking Loss (Pair Ranking and Triplet Ranking Loss)
Pytorch for Beginners #18 | Loss Functions: Ranking Loss (Pair Ranking and Triplet Ranking Loss)
Pytorch for Beginners #17 | Loss Functions: Classification Loss (NLL and Cross-Entropy Loss)
Pytorch for Beginners #17 | Loss Functions: Classification Loss (NLL and Cross-Entropy Loss)
Pytorch for Beginners: #16 | Loss Functions - Regression Loss (L1 and L2)
Pytorch for Beginners: #16 | Loss Functions - Regression Loss (L1 and L2)
Pytorch for Beginners: #15 | Pytorch Containers - nn.ParameterDict
Pytorch for Beginners: #15 | Pytorch Containers - nn.ParameterDict
Pytorch for Beginners #14 | Pytorch Containers - nn.ParameterList
Pytorch for Beginners #14 | Pytorch Containers - nn.ParameterList