Abstract: Cooking is a daily chore for many individuals and hence can become a monotonous activity. Sometimes it is difficult for one to decide what new & interesting can be cooked from the available ingredients. Lack of culinary expertise can lead to disproportionate use of ingredients resulting in wastage. Also while cooking, one’s hands are unclean to be able to look the recipe in their smart device or recipe books. For beginners cooking can also become a hassle because they might not know names of many ingredients. Our proposed system intends to help everyone with their daily cooking. Using our application one will be able to escape their monotonous cooking routine by using ingredients detection system along with recommendation model. Using our application user will be able to scan the available ingredients through which we will recommend best suitable recipe for them. For detecting the ingredients we will apply CNN algorithm with parameter optimization. CNN is the state-of-theart approach to the deep learning, with significantly higher accuracy then traditional support-vector-machine-based algorithm. Our application will store the detected ingredients of the user in the database and recommend recipe accordingly in the home page. Further recommendation on the home page would be based on the historical patterns of the user, while recommending we will be using various factors such as cuisine preference, ingredients, cooking time, etc. Using NLP we will serve the voice control feature to the users through which they will be able to hear the recipe at their own pace, in case their hands are unclean. Through NLP our motive is to overcome the regional barrier so anyone unfamiliar with English will also be able to use our application and can experience the culture of different regions through their cuisine. Keywords: object detection, deep learning, convolution neural network, recipe recommendation, natural language processing, voice assistance, hybrid based recommendation.