Which ML/DL Projects Can Help Beginners Master Concepts?

What are the projects suggested to master the concepts of ML/DL? I am a beginner and have completed specializations in both ML and DL. Now, I am looking for project suggestions to master the concepts, so please give me suggestions.


Here are some common projects you can try:

  1. A classification model using text features extracted from text (e.g., Sentimental Analyzer, or Spam email / comment detections)
  2. Train a model based on the CNN architecture to classify the images (e.g., Classifying cat, dog, bird)
  3. A simple recommender system that predicts user ratings based on previous ratings and other users’ rating data. You can use a SVD (Singular Value Decomposition) model as a simple implementation

You can also check out Kaggle Competition or Dataset to check out new ideas.

For advanced projects, you can try fine-tuning an existing big model such as ResNet, Llama


Image Classification with CNNs: Implement a convolutional neural network (CNN) to classify images into different categories. Start with a simple dataset like MNIST or CIFAR-10, then gradually move on to more complex datasets like ImageNet.

Sentiment Analysis on Text Data: Build a sentiment analysis model using natural language processing (NLP) techniques. Use techniques like word embeddings (e.g., Word2Vec or GloVe) and recurrent neural networks (RNNs) or transformers to classify text data into positive, negative, or neutral sentiments.

Predictive Analytics with Time Series Data: Work on a time series forecasting project where you predict future values based on historical data. Use techniques like autoregressive integrated moving average (ARIMA), recurrent neural networks (RNNs), or long short-term memory (LSTM) networks for time series prediction.

Object Detection and Localization: Implement an object detection model to detect and localize objects within images. Use popular frameworks like TensorFlow Object Detection API or YOLO (You Only Look Once) for this project.

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