| • Linear and Logistic Regression |
• Data Sampling |
• Word Vectors/Embeddings |
| • k-Nearest Neighbors |
• Data Imbalance |
• NLP Tasks |
| • Clustering |
• Standardization vs. Normalization |
• Preprocessing |
| • Support Vector Machines (SVM) |
• Learning Paradigms |
• Tokenization |
| • Naive Bayes |
• Xavier Initialization |
• Data Sampling |
| • Decision Trees and Ensemble Methods |
• Padding and Packing |
• Neural Architectures |
| • ML Algorithms Comparative Analysis |
• Regularization |
• Attention |
| • DL Architectures Comparative Analysis |
• Gradient Descent and Backprop |
• Transformers |
| • Prompt Engineering |
• Activation Functions |
• Token Sampling Methods |
| • Generative Adversarial Networks (GANs) |
• Loss Functions |
• Encoder vs. Decoder vs. Encoder-Decoder |
| • Diffusion Models |
• Fine-tuning Models |
• Language Models |
| • Graph Neural Networks |
• Splitting Datasets |
• Overview of Large Language Models (LLMs) |
| • Attention |
• Batchnorm |
• Overview of Vision-Language Models (VLMs) |
| • Separable Convolutions |
• Dropout |
• LLM Alignment |
| • Inductive Bias |
• Double Descent |
• Machine Translation |
| • Convolutional Neural Networks |
• Fine-tuning and Evaluating BERT |
• Knowledge Graphs |
| • Reinforcement Learning |
• Training Loss > Validation Loss? |
• Hallucination Mitigation |
| • Multiclass vs. Multilabel Classification |
• SVM Kernel/Polynomial Trick |
• AI Text Detection Techniques |
| • Mixture-of-Experts |
• Bias Variance Tradeoff |
• Named Entity Recognition |
| • State Space Models |
• Gradient Accumulation and Checkpointing |
• Textual Entailment |
| • Agents |
• Parameter Efficient Fine-Tuning |
• Retrieval Augmented Generation (RAG) |
| • Quantization |
• Hypernetworks |
• LLM Context Length Extension |
| • Model Acceleration |
• Distributed Training Parallelism |
• Document Intelligence |
| • Cross Validation |
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• Personalizing Large Language Models |
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• Code Mixing and Switching |
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• Large Language Model Ops (LLMOps) |
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• Convolutional Neural Networks for Text Classification |
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• Relationship between Hidden Markov Model and Naive Bayes |
