NLP projects for beginners

Here is the content in an immersive summer camp designed specifically for students in grades 9 and 10 who are eager to explore Natural Language Processing (NLP) in machine learning for the first time. This project-oriented camp will introduce participants to the fascinating world of NLP and guide them through various stages of sentiment analysis using Twitter data.

Throughout the camp, students will delve into the foundations of NLP and machine learning, with a focus on sentiment analysis. They will learn how to preprocess textual data using TFIDF (Term Frequency-Inverse Document Frequency) and gain hands-on experience with supervised classification techniques such as Naive Bayes (NB), Support Vector Machines (SVM), and Logistic Regression (LR). These techniques will enable students to analyze the sentiments expressed in tweets and understand the underlying sentiments conveyed by the text.

As part of the project, students will also explore model persistence by saving their trained models using pickle files. They will learn how to reload these models in a new Jupyter notebook within Google Colab, facilitating seamless experimentation and analysis. By utilizing confusion matrices, students will compare different approaches and evaluate the effectiveness of their sentiment analysis models.

Additionally, participants will have a unique opportunity to apply the ChatGPT API, which utilizes deep learning models developed by deeplearning.ai. In the first step, they will interact with the Language Learning Model (LLM) to apply sentiment analysis. This will allow them to explore the capabilities of the pre-trained model and observe its performance on various text inputs. In the second step, they will ask the agent to learn a supervised mapping between the text and sentiments provided in a CSV file, further expanding their understanding of supervised learning in NLP.

In the final phase of the project, students will venture into reinforcement learning with human feedback (RLHF). They will have the chance to provide feedback in a few-shot learning manner, helping the model identify false positives or false negatives and improve its accuracy. By observing and comparing the results obtained through RLHF, students will gain insights into the iterative learning process and the power of human feedback in training NLP models.

At the end of the summer camp, participants will have acquired a solid foundation in NLP and machine learning, specifically in sentiment analysis. They will leave with practical skills in preprocessing text data, applying various supervised classification techniques, utilizing model persistence, and exploring the potential of reinforcement learning in NLP. Join us for an engaging and enriching experience where you can unleash your potential in the exciting field of NLP and machine learning!

To enrol in similar AI/robotics camp, please visit this course.

AI/Robotics specialization

First choose from 10 hours from different levels. Then choose your first session time. The next 10 sessions are in the following week at the same time.

From: $500.00

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Here is a video explaining the project.