Nowadays, Artificial Intelligence is pervasively observed in the entire industry. Be in automobile, transport scheduling, manufacturing, farming, healthcare, beauty or finance, AI has become the necessity to materialize the objects and remodel them to become human aid. Team of Agile Infoways have analyzed in-depth AI & ML and understood the gravity of integrating this heavy solution via implementing Python.
Let’s understand how AI is different from ML in brief.
What’s AI?
Artificial Intelligence (AI) is all about machines or apps acquiring intelligence just like humans, performing – planning, learning, problem-solving, motion, manipulation, reasoning, knowledge representation using Neural networks, Natural Language Processing, and Deep Learning.
What’s ML?
Machine Learning (ML) is a program, which enhances the self-learning capability of machines or apps by feeding plenty of instructions or data, resulting in build-up logic, improvised analytical quality, and data clustering property.
AI & ML Frameworks Which Satisfy Your Needs
Laravel being a combination between logic and creative framework provides
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This chatbot uses NLP ( Natural Language Processing ) and Tensorflow at its core. The heart of this chatbot lies at the dataset which includes questions and answers related to the field of use. Chatbot is trained on this dataset, hence the quality of this dataset determines the quality of the chatbot response.
The usage of the system is to provide meal planning based on the allergies, food preferences and test reports. Any change in the value of test report, will affect the user meal planning. System allows custom meal planning which will be done by the Admin. While creating the meal plan, system shows substitute of a meal which can be good according to user reports, allergies and food preferences. Technology stack: Pandas:pandas is useful for data manipulation and analysis. Numpy: numpy is useful for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Matplotlib: matplotlib is a plotting library for the python.It provides an object-oriented API for embedding plots into applications. Sklearn: sklearn is useful for various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Graphviz: graphviz facilitates the creation and rendering of graph.