suggest ingredients based on recipe title
If the user inputs a title, then you could construct a system which finds the most similar titles in the corpus, and outputs the ingredients in the retrieved recipes. Some ideas below:  

1) Represent the titles in a common vector space using a vocabulary-based vectorization and use Jaccard or Cosine similarity to find the most similar titles.  examples of similarity measures

2) Convert the words in the title to their respective word-embeddings using FastText, GloVe, or Word2Vec (publicly available), and then use cosine distance or  word-movers distance to find the most similar titles. example of publicly available GloVe word embeddings 

3) Create sentence embeddings for the title by taking the average of the word embedding vectors or using InferSent embeddings, and then use a distance function to find the most similar titles. InferSent repository link

spaCy is a good Python package for performing these type of NLP tasks link