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You should definitely go with Julia. It has steeper learning curve than python, but it is way more powerful. As for the ecosystem, you shouldn't worry about that much: DataFrames.jl and friends is way better than pandas, MLJ.jl (https://github.com/alan-turing-institute/MLJ.jl) and FastAI.jl(https://github.com/FluxML/FastAI.jl) are great frameworks for regular ML and deepnet. And if at any point you get a feeling that you need some python library, you can always plug it in with PyCall.jl(https://github.com/JuliaPy/PyCall.jl).
You should definitely go with Julia. It has steeper learning curve than python, but it is way more powerful. As for the ecosystem, you shouldn't worry about that much: DataFrames.jl and friends is way better than pandas, MLJ.jl (https://github.com/alan-turing-institute/MLJ.jl) and FastAI.jl(https://github.com/FluxML/FastAI.jl) are great frameworks for regular ML and deepnet. And if at any point you get a feeling that you need some python library, you can always plug it in with PyCall.jl(https://github.com/JuliaPy/PyCall.jl).
You should definitely go with Julia. It has steeper learning curve than python, but it is way more powerful. As for the ecosystem, you shouldn't worry about that much: DataFrames.jl and friends is way better than pandas, MLJ.jl (https://github.com/alan-turing-institute/MLJ.jl) and FastAI.jl(https://github.com/FluxML/FastAI.jl) are great frameworks for regular ML and deepnet. And if at any point you get a feeling that you need some python library, you can always plug it in with PyCall.jl(https://github.com/JuliaPy/PyCall.jl).